",isbn:"978-1-80355-367-2",printIsbn:"978-1-80355-366-5",pdfIsbn:"978-1-80355-368-9",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"d3a491e5194cad4c59b900dd57a11842",bookSignature:" Vladimir V. Kalinin",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11782.jpg",keywords:"Variety of Traits, Historical Remarks, Modern Definitions and Descriptions, Personality Disorders, Comorbid Psychopathology, Depression, Anxiety, Obsessions, Delusion, Treatment of Personality Disorders, Phenomenology of Personality Traits, Delusional Symptoms",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 9th 2022",dateEndSecondStepPublish:"May 12th 2022",dateEndThirdStepPublish:"July 11th 2022",dateEndFourthStepPublish:"September 29th 2022",dateEndFifthStepPublish:"November 28th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"14 days",secondStepPassed:!0,areRegistrationsClosed:!1,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:'A researcher with over 300 publications in psychopathology, psychopharmacology, neuropsychiatry, and epileptology, a member of the Russian Society of Psychiatry, and the Russian Society of Epileptology. Dr. Kalinin\'s biography is included in Marquis "Who’s Who in Medicine and Healthcare" (2006-2007); Who’s Who in Science and Engineering 2008-2009"; "Who’s Who in the World" (2010, 2011), and in the Cambridge International Biographical Centre.',coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"31572",title:null,name:"Vladimir V.",middleName:null,surname:"Kalinin",slug:"vladimir-v.-kalinin",fullName:"Vladimir V. Kalinin",profilePictureURL:"https://mts.intechopen.com/storage/users/31572/images/system/31572.png",biography:"Vladimir V. Kalinin was born in1952 into a family of physicians in Orenburg (Russian Federation). He obtained an MD from Moscow State Medical Stomatological University in 1976. In 1976-1977 he completed an internship in Psychiatry. 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1. Introduction
Microbes are known to human civilization due to their beneficial and lethal effects. When the symbiotic relation of microorganisms goes beyond the limit, they may cause pathogenic infections and diseases, causing damage to the body and sometimes leading to death: this is a major concerning issue especially in developing countries. The determination of exact site of infection in the body is very critical for curing the pathogenesis caused by bacteria at their early stage. Antimicrobial agents especially antibiotics, which are either obtained from natural sources or through total synthetic procedures, are practiced against pathogens. Antibiotic may be obtained naturally from living organism (e.g., fungi, actinomycete, and bacillus species), prepared synthetically and semisynthetically in the laboratory. Its mechanism of action is divided into two spectrums (narrow and broad-range spectra). Broad-spectrum antibiotics act against both Gram-positive and Gram-negative bacteria [1]. A good antibiotic should have the following characteristics: long shelf life, nontoxic to human body, soluble in the body fluid, low cost, show long-lasting antibacterial effect, and low possibility of bacterial resistance to the agent. However, all these standard parameters for an ideal antibiotic are difficult to meet, while developing synthetic antibacterial agents that is the reason a big threat is being felt from pathogenic bacterial resistance which is the main public health-related issue, all over the globe [2]. This appeared during the last decade in a more prominent way which mainly originated either due to wrong identification of bacterial strain and prescription of antibiotic or due to imbalance use of antibacterial agents. The transmission of bacterial resistance among the individuals and across the geological border is one way of antimicrobial resistance [3]. Further, on the other way, to handle the bacterial resistance threat, the pipeline of the development of new synthetic antibacterial agents is gradually drying up. And it might be possible, on the bases of continuously increasing level of bacterial resistance; at some stage pathogenic bacteria halt antibiotic therapy—that stage will be not good in the history of human being [4].
Antioxidants such as polyphenols, vitamins, and carotenoids are the organic compounds mainly extracted from natural sources and dominantly involved in living defense system. Due to continuously increasing resistance to synthetic antibiotics, there is an urgent need to shift our focus toward natural antioxidant-based antibacterial products due to their vast chemical diversity which provide potent therapeutic effect and make the microbes unable to copy them for creating resistance. Out of many natural products and antioxidants which are showing great healthy impact on human beings, polyphenols have been reported as natural agents that fight as antioxidants, antibacterial, anticancer, anti-inflammation, and antiviral agents. We, in this chapter, tried to review the role of antioxidants as natural antibiotics. In the following section, we will discuss the inflammation and infectious process and how antioxidants play their role in fixing them. Then we will also discuss antibacterial mechanism of natural antioxidants as antibiotics in animal bodies.
2. Inflammation and infection
Figure 1.
An estimation of deaths caused by bacterial infection worldwide [5].
Pathogens like bacteria are responsible for the infection or inflammation in animals. These infections may be mild inflammation which is hardly noticeable or which appeared to human being in history as a big threat. According to one estimation, based on growing bacterial resistance, up to 2050, the death rate due to bacterial infection may increase to 390,000 in Europe and similarly all over the world as shown in Figure 1. Inflammation is a nonspecific immunological response by the organism’s body to any trauma, neoplasm, autoimmune attack, or invading of the microbes. At the site of inflammation, several processes can be noticed such as blood supply increase and leakage of cellular fluid and small molecules, and protein penetration may take place. In the case of acute injury, body defense mechanism, i.e., leucocyte and plasma protein migration to the site of infection become activated. Neutrophils invade bacteria when seeking entrance in the body and prevent the body from further infection. The process of infection starts within a second or minute and prolongs to hours or days to heal. It causes the sequential symptoms, like inflammation, redness, warmth, and pain, which consequently affect the functions of the tissue or organ. Inflammation may be a nonspecific process, but infection consists of stepwise progress in inflammation which might be chronic if it could not be addressed timely.
3. Types of infection
Infections can be categorized as viral, bacterial, fungal, protozoan, prion, and parasitic. Some viral infections are influenza, rotavirus, chicken pox, HIV, and herpes. Pneumonia, tetanus, cellulites, chlamydia, gonorrhea, etc. are the common bacterial infections. Fungal infections are ringworm, candidiasis, and athlete’s foot. Malaria and African sleeping sickness are common protozoan infections transmitted through plasmodium and tsetse fly, respectively. Prion is the poisonous entities or protein infection particles which cause fatal neurodegenerative disease. Amebiasis, dysentery, and coccidiosis infections are caused by parasites. Antibiotics are the major agents to cope and fix these infections. There are mainly two types of antibacterial agents, i.e., synthetic antibiotics and natural antibiotics. In the following section, we will discuss antibiotics, natural antibiotics, and their mode of action.
4. Antibiotics
In the ancient times, it is believed that antibiotics were the chemicals released by microorganisms, causing prompt deleterious effect on humans. However, later this notion was reversed, i.e., these compounds were used against microbes instead of isolating from them. Antibiotics are generally of two types, bactericidal which kill the bacterial cell and bacteriostatic which inhibit the bacterial growth and may kill the bacteria. The first antibiotic was discovered by Alexander Fleming in 1928 from Penicillium notatum, a soil-inhabiting fungus, and the clinical trials on humans are conducted in 1940. There are five generations of different classes of antibiotics, up till now, which have been discovered and are in clinical practice.
5. Natural antioxidants as antibiotics
The increased resistance of pathogenic microorganism against antibiotic becomes a major issue around the globe from the last decade. To overcome this serious problem, it is necessary to discover a new world of antimicrobials, which are not only beneficial in bacterial infection but show long-lasting effect by boosting the immunity of the body. However, we do not skip the usage of previously practiced antibiotics as some of them show a very effective result in bacterial infection, but there is a need of advanced or may say strong antibacterials whose chemical makeup bacteria cannot be copied.
Plant synthesizes a variety of secondary metabolites (phytochemicals) which are involved in plant defense mechanism, and it is recognized that major classes of these molecules have beneficial effects on health including antioxidants and antimicrobial. The attractive antioxidant as well as antibacterial activity of phytochemicals seeks attention as it may replace the synthetic antioxidants, which cause deleterious effect on human health such as cancer. The plant kingdom is rich in various phytochemicals like phenolic acid, flavonoids, gingerol, curcumin, etc.
Phenolic acids and flavonoids are a very important class of antioxidants as it directly affects bacterial growth and causes hindrance in their pathogenic activity. The mechanism of action of antioxidants as antibacterial is still not fully understood, but some researches reveal that the attributable antibacterial activity involves three basic mechanisms: outer membrane permeability, cytoplasm leakage, and inhibition of nucleic acid formation. The interaction of polyphenols with nonspecific forces like hydrogen bonding and hydrophobic effect lipophilic forces as well as by covalent bond formation was related to microbial adhesion and enzyme and cell envelope transport protein. The antibacterial activity of polyphenols may also due to the capacity of these compounds to chelate iron, vital for the survival of almost all bacteria. Polyphenols rupture the wall, increase the permeability of cytoplasm membrane, and release lipopolysaccharides (LPS) [6].
The cell wall composition of Gram-positive and Gram-negative differs significantly as Gram-positive bacteria have thick layer of peptidoglycan along with lipoteichoic acid but lack of outer membrane. Gram-negative bacterial outer membrane consists of phospholipid, protein, and LPS and a thin layer of peptidoglycan. Both Gram-negative and Gram-positive bacterial cell walls play a very important role in osmotic protection of cell. Any damage to cell wall will decrease the tolerance of cell against osmotic pressure and ionic strength. Many researchers have demonstrated that the interaction of polyphenols with bacterial cell wall is different for Gram-negative and Gram-positive bacteria. Different interaction cites for antibacterial agents in variety of bacterial strains are shown in (Tables 1–4).
Table 1.
Natural antioxidants and their role in inhibiting bacterial growth in living system showing interaction between the bacterial cell wall and with cell membrane.
Table 2.
Natural antioxidants and their role in inhibiting bacterial growth in living system showing metal ion deficiency due to chelating ability, microbial enzyme inhibition and substrate deprivation and other inhibition mechanism.
Table 3.
Purified antioxidants extracted from plant sources and their antibacterial potential: phenolic acid, flavones, flavanonols, catechins, and vitamins.
Table 4.
Purified antioxidants extracted from plant sources and their antibacterial potential: chalcone and flavanone.
6. Mechanisms of action
The activity of antioxidants against bacterial inflammations is being progressively recognized. They also work synergistically with current antibacterial agents against the resistant strains of bacteria. The diversity in the structure of natural products makes it impossible for bacteria to copy its functional moieties, unlike the synthetic agents. The structure of antioxidants holds the key role in determining the antibacterial activity. Different groups of researchers investigating the relationship between flavonoid structure and their antibacterial activity generalized that active compounds share common structural features. Moreover, the unique structural features may be essential for flavonoids to gain adjacency or uptake into the bacterial cell. Like, polyhydroxylated flavonoids show more pronounced antibacterial activity than mono-hydroxylated or non-hydroxylated flavonoids. Structural similarity among flavonoids is too dominant that there are three probable hypotheses regarding their mechanism of action:
Flavonoids of same structure take same mechanism.
All flavonoids follow multiple mechanisms of actions.
All flavonoids have same sole mechanism of action.
According to a recent development, the study of mechanism of actions is not that reliable as it was assumed earlier. Like epigallocatechin gallate only induce clumping of FabG enzyme and have no such effect on other enzymes. Another such development is that flavonoids cause aggregation of bacterial cells. Clumping of bacterial cells on treatment with flavonoids causes reduction in surface area of bacterial population which reduce the oxygen consumption by bacteria (interruption respiratory chains). Reduction in surface area of cells decrease the nutritional uptake like uridine and thymidine (specify nucleic acid inhibition). Moreover, the prospect of baffling and the cause and effect of mechanisms of actions exist. For example, the interruption of membrane integrity by an antibacterial agent will impart negative effects on proton-motive force that directly influence the synthesis of ATP and solute transport into the bacterial cell. The deterioration of bacterial capability to produce energy and to attain nutrients results in declining capability of bacterial cell to make DNA and peptidoglycan. So, one mechanism of action may be misunderstood as multiple.
Correspondingly, if any enzyme of bacteria-like DNA gyrase is obstructed by an antibacterial agent, then this swift automated cell death and lysis. Likewise, the antibacterial agent that impedes the synthesis of nucleic acid may be misinterpreted as the agent that alters the cytoplasmic membrane functions [7].
The following mechanisms of actions are attributed to the antibacterial action of flavonoids as reported by different groups of researchers:
Impairment of membrane functions
Alteration of cytoplasmic membrane fluidity
Inhibition of cell wall formation
Inhibition of cell membrane formation
Interruption of synthesis of nucleic acid
Inhibition of respiratory metabolism
The mechanisms of action of antioxidants as an antibacterial are shown in Figure 2.
Figure 2.
The schematic layout demonstrating the natural antioxidant role as antibacterial: (a) representing inhibition of energy metabolism; (b) representing disruption of membranes; and (c) representing interruption in nucleic acid synthesis.
6.1 Inhibition of nucleic acid synthesis
Among the classes of antioxidants, flavonoids significantly show inhibitory activity against nucleic acid synthesis. Interaction of flavonoids with DNA- or with ATP-binding site of gyrase finally leads to the inhibition of nucleic acid synthesis as shown in Figure 2. Metabolism of DNA in bacteria comprises transcription, recombination, DNA replication, and transport of genetic information. A vital enzyme to control vigorous changes of nucleic acid is DNA gyrase. Gyrases, characteristic and crucial bacterial enzymes that change the topology of DNA, are the amiable aim to hit for the antibacterial agents. DNA gyrase, in a reaction that depends on ATP, enhances the supercoiling of DNA of bacteria, and its inactivation leads to bacterial death. Estimation of DNA supercoiling is the important parameter in assessment of flavonoids activity to inhibit DNA gyrase. It has two subunits, gyrase A that takes part in DNA breakage-resealing and gyrase B that is involved in the hydrolysis of ATP, the driving force for the DNA supercoiling. The topoisomerase (DNA gyrase) inhibitors form a cleavable complex of agent-topoisomerase-DNA or interfere with the gyrase binding to DNA (see Table 2).
6.1.1 Kaempferol and PMFs
Kaempferol show the strongest antibacterial activity (MIC50 = 25 μg/ml) against E. coli DNA gyrase. It inhibits the activity of gyrase enzyme that holds the key role in DNA supercoiling and bacterial growth.
Structure of Polymethoxylated flavones
Polymethoxylated flavones (shown in structure) usually found in citrus peel possess broad spectrum antimicrobial activity. It shows antibacterial activity against E. coli and S. aureus with IC50 values ranging from 1.45 to 1.89 mg/ml [8] (see Table 3 for MIC values).
6.1.2 Quercetin
Quercetin is one of the ubiquitous flavonoids, impedes the DNA supercoiling, and causes DNA to cleave. Quercetin encourages DNA scission by forming gyrase-DNA-quercetin cleavable complex. Cleavage of DNA was promoted at quercetin concentration above 80 μM in the presence of gyrase, and at 640 μM the maximum cleavage was obtained [9]. MIC values of quercetin are listed in Table 3. Quercetin obtained from yellow onion skin has inhibitory effect on antibiotic-resistant bacteria H. pylori. Sulfur and quercetin have synergistic growth inhibitory effect with beta lactam, a very functional antibiotic [10].
Structure of quercetin
Mode of action of quercetin inhibition includes two mechanisms:
First inhibition pathway involves rivalry at binding site of ATP at gyrase B that prevents DNA supercoiling. The second mechanism involves binding to DNA that stabilizes DNA topoisomerase II complex causing DNA to cleave [11]. MIC values for different bacterial strains are listed in Table 3.
6.1.3 Glycosylated flavones
Glycosylated flavones (isolated from cottonseed flour) promote topoisomerase IV-dependent cleavage of DNA in E. coli. Rutin is the most potent glycosylated isoflavone in exciting topoisomerase IV-dependent cleavage of DNA (CC50 = 1 μg/ml). It blocks the catalytic activity of type II topoisomerase in addition to alleviate the cleavable complex. At CC50 = 64 μg/ml, rutin inhibited the decantation action of topoisomerase IV.
6.1.4 Catechins
Catechins like epicatechin, epigallocatechin, epicatechin gallate, and epigallocatechin gallate (structure is shown below) inhibit ATPase action because the ATP-binding site of B subunit of gyrase shares the structural similarity with these catechins. So, owing to this similarity with ATP-binding site, the catechins occupy these sites and as a result inhibits of ATPase activity. Catechins inhibit the ATPase activity in the following order, EGC < ECG < EGCG, while EC had no affect at all (for MIC values see Table 4) [12]. ATP hydrolysis provides vigorous force for DNA supercoiling. The inhibition of ATPase activity by catechins prevents ATP hydrolysis. In this way the DNA supercoiling is affected and so the bacterial growth.
Catechin based antioxidants
6.1.5 Soybean isoflavone
SI (soybean isoflavone) could alter the supercoiling of double-stranded DNA could be altered by affecting DNA topoisomerase. By increasing the concentration of soybean isoflavone, the supercoiling activity increases and the quantity of linear and open circular DNA decreases.
At 6.4 mg/ml concentration, SI significantly inhibited the activity of both topoisomerase I and II so stops the bacterial growth by affecting nucleic acid synthesis. Topoisomerase inhibitors form a drug-gyrase-DNA cleavable complex or disrupt the topoisomerase binding to DNA [13].
6.1.6 Genistein
Genistein is an isoflavone (shown in structure below) and characteristic of other flavonoids, apigenin, daidzein, and kaempferol for common use on the laboratory strains bacterial species like B. subtilis, E. coli, and V. harveyi. Addition of this flavonoid to bacterial cultures imposes drastic effects on the synthesis of DNA and RNA in almost 15 min [14].
Three hours after addition, genistein caused the bacterial cells to become elongate that cause troubled cell division and chromosome replication. MIC values are listed in Table 3.
Protein synthesis was also significantly inhibited by genistein but was delayed a little, suggesting that repression of translation by genistein is secondary effect.
6.2 Disruption of membranes
The outer bacterial membranes safeguard the bacterial cells from harsh environment, causing them to survive in extreme conditions. The inner membrane or the so-called cytoplasmic membrane regulates the uptake of solutes and minerals into the cell as well as the transport of proteins and other macromolecules. The alteration in membranes causes many adverse effects on functions of bacterial cells that might be very important for bacterial integrity, like uptake of mineral ions and nutrients. To study the membrane effects of antioxidants, fluorescence polarization methods using model membranes (consisting of two component: DPPC and POPC) are used. Fluorescence polarization increasingly alters in correspondence with reduction in membrane fluidity. MIC values are given in Table 3.
The antioxidants like polyhydroxyl flavans and catechin of green tea hinder the development of certain bacteria and affect Gram-positive and Gram-negative bacteria by damaging the structure of membranes of the bacterial cells (see Table 1).
6.2.1 Sophoraflavanone G
Sophoraflavanone G, a phytochemical with intensive antibacterial activity, shows very low MICs (1.56—12.5 μg/ml) against Gram-positive bacteria than Gram-negative bacteria by altering membrane functions. Increased polarization in DPPC and POPC liposomes implies that sophoraflavanone G decreases membrane fluidity (for MIC value see Table 4) [15].
6.2.2 Catechins
The pathogenicity of Gram-negative bacteria is linked to the lipopolysaccharide layer (reduce the sensitivity against antibacterial agents). That is why, the antibacterial agents demonstrate more activity for Gram-positive bacteria. Catechins intermingle and target bacterial membrane protein, fatty acid synthase, beta lactamase, and such other bacterial enzymes. Antibacterial catechins were reported to alter membrane fluidity [16]. Tea catechins impart specific agitation in the well-organized phosphatidylcholine and phosphatidylethanolamine bilayers that makeup membranes of bacteria. Epigallocatechin gallate (EGCG), a polyphenol obtained from green tea, black tea, and cocoa shows intensive activity, perturbs membranes of bacteria, and causes leakage of membranes isolated from E. coli. The antibacterial effects result from the interaction of catechins which interacts with oxygen, genes, and cell membranes, and these interactions produce their antibacterial effects. MIC values are given in Table 3.
EGCG binds straight to the peptidoglycan of S. aureus, affects integrity of cell and thereby decreases the acceptance of the cell to high osmotic pressure and less ionic strength. EGCG induces changes in morphology of Gram-negative bacteria depending on the acquittance of H2O2 and causes oxidative stress in bacteria. Flavonoids (epigallocatechin, myricetin, quercetin; structure shown below), damage membrane protein, and coagulate cytoplasm alter constituents of fatty acids and phospholipids, weaken mechanism of energy formation and metabolism, impacts the production of RNA and DNA, and abolishes translocation of proteins [17].
Epicatechin gallate (ECG) dramatically alters the physical properties of phosphatidylcholine (PC) and phosphatidylethanolamine (PE) bilayers. They cause leakage from the membranes that is known to be pronounce by the presence of PE. So, at membrane level the antibacterial properties of catechins are due to their damage to PE. So, to estimate the phospholipid specificity, in the presence and absence of PE, egg yolk model was used. The results showed that only galloylated catechins affected PE and caused prominent leakage at 6.3 mol%. Protein translocation and other such processes are to some extent related to phospholipids; so, any effect on these can significantly alter the cell metabolism of bacteria [18]. Liposome membranes are damaged by EGCG and the leakage of intraliposomal CF occurs. This damage to membranes increases the permeability of catechins for catechins to penetrate in the cell. But how catechins damage the bilayer and penetrate the cell is still unanswered [19].
6.2.3 Ferulic and gallic acid
FA and GA cause severe and irreversible damage to the membranes causing constant leakage of the essential cell constituents. Different physiological terms are used to access the antimicrobial activities: MIC, MBC, and K+ release in the cell. The MIC values of ferulic and gallic acids against some bacterial strains are listed in Table 5.
Table 5.
MIC values of antioxidants against bacterial strains.
At 100 μg/ml ferulic acid and gallic acid cause 60% damage to the cytoplasmic membranes of P. aeruginosa. The uptake of propidium iodine (nucleic acid strain to which cell is impermeable) shows that FA and GA alter membrane integrity. In the outer membrane of Gram-positive and Gram-negative bacteria, porins (hydrophilic channels) are present that stops the hydrophobic substances from entering the cell. But some natural agents disintegrate the lipopolysaccharide layer and so damaging the permeability of the membrane causing nutrients to leak and effecting bacterial growth [20].
Moreover, bacterial cells have negative surface charge because of the ionic groups. The exposure to phenolic acids decreases this charge and the transport of solutes. Excess of phenolic acids cause hyper acidification that makes the cytoplasm acidic and denature the proteins present in the cytoplasm. So, the damage to membrane by acidification potentially explains the activity of phenolic acid.
Another factor that indicates the membrane damage is K+ leakage. Because the cell’s internal environment is rich in K+, any damage to the cytoplasmic membranes causes its leakage that indicates the damage as shown in Figure 2.
6.3 Inhibition of energy metabolism
In bacterial cell the energy is required for the transport of solutes, uptake of metabolites, and biosynthesis of macromolecules. This energy comes from the respiratory chains like electron transport chain. Some antioxidants inhibit the respiratory chains at any step and thus depriving the cell of the energy necessary for growth (see Table 1).
6.3.1 Reterochalcones
Reterochalcones stops the oxygen consumption in the targeted cells and inhibits the NADH oxidation in the membranes of bacteria. The electron transport chain is inhibited in between the CoQ and cytochrome c sites as shown in Figure 2. The inhibition of respiratory chains stops the supply of energy to the cells thus retarding their growth [8, 21].
7. Conclusion
There is no doubt that synthetic antibiotics show quick therapeutic effect while treating bacterial infections but in parallel imposes the threat of serious gastrotoxicity, nephrotoxicity, and bacterial resistance. All these issues required special attention because we are gradually losing the game by treating bacterial infections with synthetic antibiotics—as we discussed in previous sections, natural antioxidants in its pure (isolated from raw extracts) had showed excellent potential against common infection causing bacteria, and no study has yet been reported of bacterial resistance to these compounds which firm our enthusiasm to study natural products with the aim to replace synthetic antibiotics. Finally, we can conclude that although antioxidants work slowly against bacterial growth, directly or indirectly, their action is steady and healthy—the continuous and careful evaluation in establishing antibacterial profile of isolated antioxidant can help in the utilization of natural products against bacterial infections with negligible toxicity and the fear of bacterial resistance.
Acknowledgments
The authors are very happy to pay their gratitude to Ms. Rida Siraj (MS scholar), Ms. Afshan Kanwal (PhD scholar), and the students of Dr. Ali’s research group for their input in collecting and compiling the data for this chapter.
Conflict of interest
The authors declare “no conflict of interest.”
Thanks declarations
The authors are highly thankful to the Higher Education Commission (HEC) Islamabad and Government College University, Faisalabad, Pakistan, for providing necessary resources to complete this project.
\n',keywords:"antioxidants, antibacterial agents, infection therapy, natural antibiotics",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/66161.pdf",chapterXML:"https://mts.intechopen.com/source/xml/66161.xml",downloadPdfUrl:"/chapter/pdf-download/66161",previewPdfUrl:"/chapter/pdf-preview/66161",totalDownloads:1557,totalViews:0,totalCrossrefCites:5,totalDimensionsCites:8,totalAltmetricsMentions:0,impactScore:6,impactScorePercentile:95,impactScoreQuartile:4,hasAltmetrics:0,dateSubmitted:"September 22nd 2018",dateReviewed:"January 31st 2019",datePrePublished:"April 23rd 2019",datePublished:"November 6th 2019",dateFinished:"March 14th 2019",readingETA:"0",abstract:"The aim of this current piece of writing is to draw the attention of readers and researchers toward the natural antioxidants that can take the place of synthetic antibiotics to avoid bacterial resistance and gastrotoxicity/nephrotoxicity. Antioxidants such as polyphenols, vitamins, and carotenoids are the organic compounds mainly extracted from natural sources and dominantly involved in boosting the defense system of organisms. The main public health-related issue over the globe is ever-growing bacterial resistance to synthetic antibiotics, which is being continuously reported during the last decade. Further, the pipeline of the development of new synthetic antibacterial agents to replace the resistant antibiotics in clinical set-up is gradually drying up. This scenario originated the concept to revive the interest toward natural antibacterial products due to their chemical diversity, which provide important therapeutic effect and make the microbes unable to copy them for creating resistance. Natural products, especially polyphenols had been seen in antioxidant, antibacterial, anticancer, anti-inflammation, and antiviral activities with encouraging results. In this chapter, we will focus over the role of natural antioxidants as antibacterial agents.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/66161",risUrl:"/chapter/ris/66161",book:{id:"8008",slug:"antioxidants"},signatures:"Syed Ali Raza Naqvi, Sana Nadeem, Sana Komal, Syed Ali Asad Naqvi, Muhammad Samee Mubarik, Sajid Yaqub Qureshi, Shahzad Ahmad, Ali Abbas, Muhammad Zahid, Naeem-Ul-Haq Khan, Syed Shujat Raza and Nosheen Aslam",authors:[{id:"259190",title:"Dr.",name:"Syed Ali Raza",middleName:null,surname:"Naqvi",fullName:"Syed Ali Raza Naqvi",slug:"syed-ali-raza-naqvi",email:"drarnaqvi@gmail.com",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259190/images/system/259190.png",institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"287649",title:"Ms.",name:"Sana",middleName:null,surname:"Nadeem",fullName:"Sana Nadeem",slug:"sana-nadeem",email:"sananadeem242@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"287650",title:"Ms.",name:"Sana",middleName:null,surname:"Komal",fullName:"Sana Komal",slug:"sana-komal",email:"sanakomal30@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"287652",title:"Dr.",name:"Muhammad Samee",middleName:null,surname:"Mubarik",fullName:"Muhammad Samee Mubarik",slug:"muhammad-samee-mubarik",email:"sameech2002@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"287654",title:"Dr.",name:"Muhammad",middleName:null,surname:"Zahid",fullName:"Muhammad Zahid",slug:"muhammad-zahid",email:"zahid595@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"287655",title:"Mr.",name:"Ali",middleName:null,surname:"Abbas",fullName:"Ali Abbas",slug:"ali-abbas",email:"malikaliabbas90@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"298090",title:"Dr.",name:"Syed Ali Asad",middleName:null,surname:"Naqvi",fullName:"Syed Ali Asad Naqvi",slug:"syed-ali-asad-naqvi",email:"draliasad@gcuf.edu.pk",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"298091",title:"Dr.",name:"Sajid Yaqub",middleName:null,surname:"Qureshi",fullName:"Sajid Yaqub Qureshi",slug:"sajid-yaqub-qureshi",email:"qsajid@hotmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"298092",title:"Dr.",name:"Naeem-Ul-Haq",middleName:null,surname:"Khan",fullName:"Naeem-Ul-Haq Khan",slug:"naeem-ul-haq-khan",email:"naeemulhaq091@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"298093",title:"Dr.",name:"Nosheen",middleName:null,surname:"Aslam",fullName:"Nosheen Aslam",slug:"nosheen-aslam",email:"naslam@gcuf.edu.pk",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"303158",title:"Dr.",name:"Shahzad",middleName:null,surname:"Ahmad",fullName:"Shahzad Ahmad",slug:"shahzad-ahmad",email:"shazadahmad@gcuf.edu.pk",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"311133",title:"Mr.",name:"Syed Shujat",middleName:null,surname:"Raza",fullName:"Syed Shujat Raza",slug:"syed-shujat-raza",email:"shujat611@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Inflammation and infection",level:"1"},{id:"sec_3",title:"3. Types of infection",level:"1"},{id:"sec_4",title:"4. Antibiotics",level:"1"},{id:"sec_5",title:"5. Natural antioxidants as antibiotics",level:"1"},{id:"sec_6",title:"6. Mechanisms of action",level:"1"},{id:"sec_6_2",title:"6.1 Inhibition of nucleic acid synthesis",level:"2"},{id:"sec_6_3",title:"6.1.1 Kaempferol and PMFs",level:"3"},{id:"sec_7_3",title:"6.1.2 Quercetin",level:"3"},{id:"sec_8_3",title:"6.1.3 Glycosylated flavones",level:"3"},{id:"sec_9_3",title:"6.1.4 Catechins",level:"3"},{id:"sec_10_3",title:"6.1.5 Soybean isoflavone",level:"3"},{id:"sec_11_3",title:"6.1.6 Genistein",level:"3"},{id:"sec_13_2",title:"6.2 Disruption of membranes",level:"2"},{id:"sec_13_3",title:"6.2.1 Sophoraflavanone G",level:"3"},{id:"sec_14_3",title:"6.2.2 Catechins",level:"3"},{id:"sec_15_3",title:"Table 5.",level:"3"},{id:"sec_17_2",title:"6.3 Inhibition of energy metabolism",level:"2"},{id:"sec_17_3",title:"6.3.1 Reterochalcones",level:"3"},{id:"sec_20",title:"7. Conclusion",level:"1"},{id:"sec_21",title:"Acknowledgments",level:"1"},{id:"sec_24",title:"Conflict of interest",level:"1"},{id:"sec_21",title:"Thanks declarations",level:"1"}],chapterReferences:[{id:"B1",body:'Al-Mohanna M. Antibiotics and Chemotherapeutic Agents. 2016'},{id:"B2",body:'Moellering RC Jr. Essential characteristics of antibiotics for the treatment of seriously ill patients. Clinical Therapeutics. 1981;4(Suppl A):1-7'},{id:"B3",body:'Aminov RI. A brief history of the antibiotic era: Lessons learned and challenges for the future. Frontiers in Microbiology. 2010;1:134-134'},{id:"B4",body:'Song JH. What’s new on the antimicrobial horizon? International Journal of Antimicrobial Agents. 2008;32(Supp. 4):S207-S213'},{id:"B5",body:'https://amr-review.org/sites/default/files/AMR%20Review%20Paper%20-%20Tackling%20a%20crisis%20for%20the%20health%20and%20wealth%20of%20nations_1.pdf'},{id:"B6",body:'Papuc C et al. 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Phytomedicine. 2000;7(2):161-165'},{id:"B16",body:'Tsuchiya H et al. Comparative study on the antibacterial activity of phytochemical flavanones against methicillin-resistant Staphylococcus aureus. Journal of Ethnopharmacology. 1996;50(1):27-34'},{id:"B17",body:'Shan B et al. The in vitro antibacterial activity of dietary spice and medicinal herb extracts. International Journal of Food Microbiology. 2007;117(1):112-119'},{id:"B18",body:'Caturla N et al. The relationship between the antioxidant and the antibacterial properties of galloylated catechins and the structure of phospholipid model membranes. Free Radical Biology and Medicine. 2003;34(6):648-662'},{id:"B19",body:'Ikigai H et al. Bactericidal catechins damage the lipid bilayer. Biochimica et Biophysica Acta (BBA): Biomembranes. 1993;1147(1):132-136'},{id:"B20",body:'Borges A et al. Antibacterial activity and mode of action of ferulic and gallic acids against pathogenic bacteria. Microbial Drug Resistance. 2013;19(4):256-265'},{id:"B21",body:'Cushnie TPT, Lamb AJ. Antimicrobial activity of flavonoids. International Journal of Antimicrobial Agents. 2005;26(5):343-356'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Syed Ali Raza Naqvi",address:"drarnaqvi@gmail.com",affiliation:'
Department of Chemistry, Government College University, Pakistan
Department of Biochemistry, Government College University, Pakistan
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1. Introduction
1.1 Motivation
Physical inactivity, particularly among aging adults and home-bound individuals with chronic conditions and/or disabilities, is a major national concern in the United States [1]. Regular physical activity, defined as 150 minutes of moderate physical activity per week [2], supports improved health and decreases the risk of obesity and chronic disease for people of all ages and abilities. Physical exercise also has important benefits for individuals with chronic health conditions such as arthritis [3]; depression [4, 5]; stroke [6]; lower-limb disabilities [7]; fibromyalgia [8, 9]; cardiopulmonary difficulties [10, 11]; multiple sclerosis [12]; Parkinson’s disease [13]; and vestibular disorder [14]. In addition to physical benefits, engagement in physical activity provides psychological benefits for these individuals [15, 16]. Despite this evidence, less than half of all adults get the recommended amount of physical activity on a regular basis [17]. This issue becomes extremely serious during Coronavirus (COVID-19) pandemic [18]. The associated economic impact of physical inactivity is significant: annual health-care expenses are estimated at $860 billion for community-dwelling adults 50 years or older [2] with still additional workforce impacts [19]. These impacts are compounded by the fact that 80 percent of chronic conditions can be prevented or managed with regular physical activity [2]. Therefore, there is an urgent need to develop practical innovative exercise methods that engage individuals at all ages, including those with chronic health condition(s) and/or disability, increase regular physical activity levels, and translate to improved health with optimal functional ability and participation.
As noted above, typical physical activities may not always be feasible for individuals who suffer from disabilities or diseases, and may increase the risk of new and exacerbated chronic health conditions, compounded by advanced age. There is a critical need to tailor physical activity to an individual, based on their underlying capability, health risks, and movement goals. For example, different individuals may wish to strengthen different muscle groups, or have specific movement goals directed by a physical or occupational therapist.
In order to achieve those goals, we propose a Versatile, Individualized, and Generative ORchestrator (VIGOR) to motivate the movement of people (particularly those with limited mobility) [20]. To Help, Push, and Coach (HPC) users with various chronic health conditions to participate in restorative physical activities in the most effective way, the VIGOR system is designed to adapt to ensure an individualized experience that accounts for the personal, environmental, and social/cultural characteristics of the user [21]. Figure 1 compares VIGOR with its competitors. The proposed VIGOR is unique in that it can provide a fully personalized user experience. Software products in the industry using virtual technology to encourage engagement in physical activity [23, 24, 25] include SaeboVR (www.saebo.com/saebovr), Nintendo Wii, and Verapy Therapy VAST (vast.rehab). Similar software products in Academia include OpenSim (opensim.stanford.edu) and QuaterNet (Facebook AI Research). Unlike those products, VIGOR integrates Tai-Chi, the traditional mind–body wellness and healing art [26, 27], with a series of data-driven computing technologies that will provide customized restorative physical activities for individuals with a broad range of chronic conditions and functional abilities. Our premise is that a user-friendly movement HPC system that may be conveniently utilized in sitting or standing positions, will empower individuals to increase their regular physical activity levels, and thus, improve health, functional ability, and participation in activities of everyday life. In this way, VIGOR emerges as an innovative, individualized and generative fitness modality that demonstrates connection of data, systems, and people for potential clinical benefits [20, 28].
Figure 1.
Motivation and rationale for the proposed VIGOR system: a comparison between existing systems and VIGOR (online video [22]).
In this research, we propose developing VIGOR within the context of Tai-Chi, a traditional mind–body wellness and healing art [26, 27, 28]. While our methods and framework can be applied to multiple exercise approaches, Tai-Chi is ideally suited to people with limited mobility, such as aging population and disabled people. Tai-Chi has documented benefits in improving balance as well as muscle strength, coordination, and endurance in multiple populations [26]. In addition, the low-impact nature of Tai-Chi is ideal for elderly individuals or groups with neuromusculoskeletal impairments. This exercise has low risks for musculoskeletal injury and joint damage while providing the many benefits of exercise.
While Tai-Chi is proven to have many health benefits, the underlying biomechanics of different choreography tailored to individual patient capabilities are difficult to identify. Knowing the “right” strategy for an individual from a kinematic trajectory alone is difficult without understanding underlying physiology. Biomechanical models can be used to determine the kinetics resulting in a desired kinematic trajectory [29, 30, 31, 32], and then to coach the patient to activate the correct muscles to work toward their movement goals. Joint kinetics are more directly mapped to underlying muscular strength and capability compared to joint kinematics [32]. Thus, the incorporation of underlying biomechanics is critical for personalization of training sessions and mobility targets.
1.2 Rationale for the VIGOR system to address aging and chronic disability
Tai-Chi is characterized by low impact, flowing, and circular movements [13, 27]. The practice of these movements requires coordination and synchronization of a calm yet alert mind and a relaxed body [15, 16, 21]. It has enormous potential for improving physical and psychological functionality for users in both clinical and non-clinical settings by allowing flowing movements that offer body and mind benefits to users [28, 33, 34].
Enabled by deep learning technology, the proposed Tai-Chi based VIGOR offers several unique advantages as an individualized, effective, sustainable, and restorative fitness modality for users with movement-based chronic health conditions. The integration of Tai-Chi with four-dimensional (4D: the sensory data includes X-Y-Z plus a somatosensory signal [35, 36]) virtual-reality technology is both innovative and feasible in that: (1) Complex human movement can be deconstructed into primitive components/modes and deep learning methods [37] can be employed to accurately formulate the spatially and temporally dependent kinetic behavior as well as reconstruct incomplete joint movement or distorted movement caused by chronic health condition(s) [38]; (2) 4D kinetic behavior can be captured and reconstructed through modern sensors, actuators, and VR/AR technologies to generate seamless human-machine interaction; (3) Despite having significant storage and computation complexity, real-time kinetic analytics is applicable over a cutting-edge big-data engine and high-performance computing platform.
1.3 VIGOR’s infrastructure
VIGOR aims to enable users an intelligent, four-dimensional (4D), partial control (e.g., virtual limb, which indicates that VIGOR can be driven by part of the inputs. In other words, VIGOR can tolerate and compensate for missing input when part of an input channel(s) is disabled), virtual-reality, and active-orthosis-enabled generative modality.
Figure 2 shows the infrastructure of the VIGOR system. A deep-learning-based virtual coach, which is trained by Tai-Chi master’s kinetic data, is the core module of VIGOR. By applying experience (obtained via deep learning) with other related knowledge such as biomechanics and medical pathology, VIGOR measures a user’s movements, evaluates his/her performance in comparison to the Tai-Chi master, and offers real-time visual and tactile feedback to the user. Far more than an on-site real-time Tai-Chi instructor, VIGOR also adapts the master movements to accommodate a wide range of mobility restrictions and improvements over time.
Figure 2.
Infrastructure of VIGOR.
The kinetic data for the Tai-Chi master and users are captured by different sensors, such as Microsoft Kinect and somatosensory sensors [39]. The fusion, transmission, storage, retrieval, management, and analytics [40] of sensory data are computationally and storage intensive. In VIGOR, an edge-computing-enabled network is exploited to connect the user with the virtual coach server. An edge server is employed to store and process the large volume of sensory data in real-time [41]. Integrated with Tensorflow, a deep learning library, VIGOR measures and predicts kinetic behavior of VIGOR users.
The system also provides the user with a multi-fold and panoramic 4D experience that includes visual, somatosensory information and direct physical support. 3D reconstruction and visualization with Unity3D allows the user to place themselves in a variety of different simulated spaces with a personalized virtual Tai-Chi coach walking them through Tai-Chi motions in a 3D world, supported by a soft-actuator based wearable device.
VIGOR is developed following “5S criteria” as follows: (1) Substantiation (or personalization) - VIGOR can provide user with personalized service according to their health condition and clinical requirements; (2) Simplicity - even those who are untrained or uneducated users can freely use VIGOR; (3) Skimpiness - only commodity hardware and software are used in VIGOR so that majority of people can afford it; (4) Scalability - VIGOR can satisfy the requirement of increasing number of users; (5) Speed - real-time response is needed to satisfy the requirement of users.
1.4 Research objectives and function modules of VIGOR
The major objective of the VIGOR is to develop a state-of-art deep learning system to help, push, and coach the people, particularly those suffering from mobile disability, so that they can get engaged in physical activities.
For the people who are not able to move due to aging, disability or health issues, a Helper is needed to support their movement, virtually or physically. This is a network completion problem, which infers missing vertices (dysfunctional joints) and edges (i.e., dysfunctional muscles/bones). Section 4 will talk about the solution to this problem.
For the people who are reluctant to move, a Pusher is needed to stimulate them through specific external audio/video/tactile stimulus (e.g., VR/AR, actuator). The reconstruction of physics stimulus will be addressed in Subsection 2.2.
For the people who do not know how to move, a Coach is needed to recognize/score their’ motion and send them real-time feedback/instruction (Subsections 3.2 and 3.3); or design individualized and optimized exercise according to their health condition or medical requirement. These two problems are motion recognition (Section 3) and generation (Section 5), respectively.
As a matter of fact, machine learning approaches ignore the fundamental biomechanics law and clinical regulations for human motion and thus may result in ill-posed problems. Additionally, deeper and wider deep neural networks (DNNs) often require large sets of labeled data for effective training and suffer from extremely high computational complexity, preventing them from being deployed in real-time systems. As a result, there is a need to incorporate domain knowledge into DNNs [42, 43]. As one of the major contributions of this project, domain knowledge will be infused into DNNs through data augmentation, customizing loss function, or embedding knowledge block into NN as an independent module (e.g., dynamics-guided discriminator in the motion choreography module).
Enabled by the deep neural network and multimodal human-machine-interaction techniques, the VIGOR system consists of the following function modules:
Real-time 4D human-machine interaction based on robust data acquisition, transmission, and re-construction methods (Section 2). It is challenging to integrate, represent and analyze heterogeneous 4D temporal data in proper data formats, which is applicable over various affordable hardware instruments. In this task, a proper uniform data format characterizing the human kinetics across heterogeneous hardware platforms is studied. In addition, to facilitate the interaction between user and VIGOR, two-way communications are investigated.
Identification of a user’s kinetic movement (Section 3). To help, push and coach (HPC) users (including people with mobile disability) in real time, VIGOR needs to identify a user’s kinetic behavior and respond users with prompt instructions. Major research challenges are (1) the normalization of the kinetics of users (including the people with limited mobility), (2) the formulation Tai-Chi movement philosophy using neural network, and (3) the metrics about movement grading. The technical contributions of VIGOR include: (1) normalizing sensory data spatially, temporally, and kinetically, and removing occlusion using spherical interpolation and Kalman filtering algorithms; (2) deriving reference Tai-Chi kinetic patterns of using temporal neural network such as long-short term memory (LSTM); (3) grading users’ kinetic behavior using entropy; and (4) enriching kinetic data using inverse dynamics theory.
Adaptive virtual limb generation (Section 4). To motivate a user who has had a limb amputated to move, VIGOR provides the user with a pleasurable sensation experience that the limb is still there by generating a virtual limb. To this end, a major challenge is the difficulty in generating the adaptive motion of the virtual limb based on the observed kinetic behaviors of functional body parts. In this task, deep neural network regression is designed for real-time virtual limb generation and then time series prediction model [44] is used to improve the consistency of generated kinetics sequence. A hierarchical visible autoencoder is developed and evaluated for the adaptive virtual limb generation according to the kinetic behavior of functional body-parts, which are measured by heterogeneous kinetic sensors. The virtual limbs can be reconstructed on VR/AR platform and active orthoses [45].
Creating individualized movement choreography (Section 5). A unique feature of VIGOR is its ability to create customized movement choreography for individual users based on their observed health conditions. One of the most challenging issues in deep learning enabled choreography is how to balance the training reliability and the creativity of neural network. In consideration of complex body action coordination in human motion, visible deep neural networks integrating biomechanics and DNNs are developed to generate Tai-Chi choreography. Specifically, knowledge-guided neural network architectures of LSTM, generative adversarial networks (GAN) [46], and their combinations with multiple data modality are designed to create customized movement choreography for individual users based on their health conditions and clinical rehabilitation requirements. New training methods based on the polynomial-based Hessian-free Newton–Raphson optimizer [47] is also created.
Each research objective along with the specific challenges and tasks will be described in more detail in Sections 2–5 individually.
2. Real-time 4D human-machine interaction
The challenge of Objective 1 is to provide real-time (prompt HPC feedback) and scalable (to support multiple-user) human-machine interaction environment based on affordable hardware instruments with heterogeneous modality. To address the challenge, real-time 4D data acquisition and two-way communication are investigated.
2.1 Acquisition of 4D sensory data
Figure 3 shows the basic input and output equipment of VIGOR. A Microsoft Kinect and a foot pressure sensor are used as input equipment to acquire kinetic data (or 4D sensory data) of an VIGOR user. Virtual reality goggles, such as the Oculus Rift or HTC Vive, tactile actuators, and active orthoses are used as output equipment that work together to depict 4D feedback to the user.
Figure 3.
Input&output instruments (the optional hardware is highlighted in light color).
2.1.1 Acquisition and processing of kinematic data
The Microsoft Kinect collects the kinematic data of the Tai-Chi master (for training purposes) and the user. Through Kinect, we can obtain joints’ transient position xyztk and corresponding Quaternion rotation [48] cosθ2sinθ2v→k, where θ is an angle around unit axis v→,t is the time, and k is the joint identifier. Quaternions [48] are considered to represent the rotation of a rigid body in 3D space using four degrees-of-freedom (DOFs).
Quaternions are superior to many other traditional rotation formulation methods because they completely avoid gimbal-lock [49]. In VIGOR, Quaternions are used in 4D reconstruction over Unity3D platform and acquisition of kinetic signal. On the other hand, as a Quaternion is specified with reference to an arbitrary axis vector it is not a good choice in rotation recognition. In VIGOR, Euler angles αβγ, which represent the angles rotating around axis Z, X, Y respectively (denoted as yawpitchroll in some literature) are adopted in gesture recognition.
VIGOR stores the captured kinetic data in JavaScript Object Notation (JSON) format, which includes joint position xyztk, quaternion rotation cosθ2sinθ2v→tk, tracking status (0: invisible; 1: referred; 2: observable), and potentially forces ftk and moments, etc. Tracking status indicates whether or not the joint is observable by the sensor. The forces and moments are derived by inverse dynamics analysis.
Due to measurement error or unavoidable occlusion, a joint is not always observable or tractable by the kinetic sensor. Spherical linear intERPolation (SLERP) [50] and Kalman filtering techniques (be discussed in Section 3.1) are employed to compensate the missing data. As illustrated in our preliminary online video [22], SLERP can effectively address those short-term missed-tracking joints (namely tracking status = 0 or 1).
2.1.2 Acquisition of tactile data
Besides Kinect, other acquisition instruments such as accelerometers, orientation sensors, and strain gauges [39] are also considered for the VIGOR system. As indicated above, a foot pressure sensor is used to obtain the ground reaction force Ft for inverse dynamic analysis. Furthermore, electromyography (EMG) [39] is selectively employed to evaluate and record the electrical activity produced by skeletal muscles. The EMG signal is characterized by a frequency range of several hertz to over 1 kHz and by amplitudes ranging from fractions of a microvolt to a few thousand microvolts. Electromyographic signals can be analyzed to detect activation level or to analyze the biomechanics of users’ movement. To acquire high-quality EMG signals from localized muscle region, identification of localized muscle region of users, noise reduction and grounding practices (to eliminate extraneous electrical noise), electrode site preparation and placement (to minimize the detection of irrelevant bioelectrical signals) and appropriate differential signal preamplification and preliminary signal conditioning (to further enhance signal-to-noise ratio) can be conducted. EMG signals can be classified to detect movements of limb. Our active/powered orthosis system, which enables users for movement, has EMG and Internal measurement Unit (IMU) sensors. Those sensors can monitor body movement and muscle activity and send the measurement data to the server.
2.2 Reconstruction of 4D data
4D kinetic feedback/instruction is reconstructed through virtual reality, tactile actuators, and motoring system that drives the active orthosis. (1) VR/AR facility, which can visualize the kinetics of human body in Quaternion format [48, 49] (acceptable by Unity3D VR/AR SDK). (2) Tactile actuators, through which VIGOR can directly guide users with somatosensory feedback. Tactile actuators potentially used in VIGOR include Eccentric Rotating Mass (ERM), Linear Resonant Actuator (LRA), Piezo, and Electro-Active polymers (EAP) with high fidelity of sensations, and excellent durability. (3) Active orthosis [51], which enables users with direct physical support through functional electrical stimulation (F.E.S) [51] or robotic exoskeletons [45].
2.3 Developing communication and edge-computing protocols
2.3.1 Real-time, two-way communication
Two-way communications are of key importance in the proposed system, since the information needs to be exchanged in a real-time manner. The challenges of the communication protocol for the proposed VIGOR include: (1) Real-time communication: Information in the VIGOR system needs to be conveyed in real time. If there is a significant delay in the communications, synchronization between the Tai-Chi master and user will be lost and the user will experience a disturbed rhythm. (2) High communication throughput: When there are many users, all the corresponding multimodal sensory data and feedback information need to be conveyed in the network, thus incurring a substantial requirement for communication bandwidth. (3) Two-way communications: The communications are between the virtual Tai-Chi master and users with mutual interactions. Therefore, it could be sub-optimal if one-way communications are considered separately. (4) Dynamics awareness: The communications may be optimized together with the physical dynamics of the virtual Tai-Chi master and users (namely the motions).
To address the above challenges, first, VIGOR can be modeled as a cyber physical system (CPS) [52, 53] and then the bandwidth can be analyzed for controlling the physical dynamics. Last, the detailed communication protocol can be designed and evaluated with the whole system.
2.3.2 Deployment of VIGOR on affordable hardware using edge computing
Edge computing enables real-time knowledge generation and application to occur at the source of the data close to user device [54, 55], which makes it particularly suitable for the proposed latency-sensitive system. An edge server can be adapted to serve multiple users through interaction with their devices. There are communication and computing trade-offs between the edge server and each user device. Data could either be locally processed at the user device or else be transmitted to and processed at the edge server. Different strategies introduce different communication costs, resulting in different delay performance. To provide the best quality of experience for users, the following tasks are involved: (1) Identification and modularization of computing tasks: the computing tasks of data preprocessing, kinetic movement recognition, and individualization of movement choreography need to be identified and the corresponding computing overheads (CPU cycles, memory) need to be determined. (2) Design, prototyping and enhancement of offloading schemes: Based on the results of bandwidth and delay analysis as well as delay performance requirement, computation offloading schemes need to be developed to determine which computing tasks should be performed locally at the user device and which computation tasks should be offloaded to the edge server. As shown in Figure 4, an illustrative concept demonstration about edge-computing-enabled VIGOR is given in our online video [56].
Figure 4.
Edge-computing-enabled VIGOR deployed on commodity hardware (demo in online video [56]).
3. Identification and scoring of user’s kinetic movement
To help, push and coach (HPC) users with movement disabilities in real time, VIGOR is featured with: (1) an enriched dataset by introducing kinetic data (specified by time series [57, 58, 59]), which is derived from the measured kinematic data, into the neural network; (2) compensating with any missing kinetic data introduced by users’ disability. Identification of a user’s kinetic behavior during movement mainly involves the following research tasks:
3.1 Preprocessing pipeline for kinetic movement identification
Data preprocessing operations play an indispensable role in VIGOR because:
Input data is of a heterogeneous nature. For example, different users have variable sizes; sensors may have various viewing angles; users may not always be located in a deterministic position; and the two time-series data sets may not be synchronized. As a result, scaling, rotating, translating, and dynamic time warping (DTW) are needed to normalize the original input data.
The input data set may be incomplete. For example, occlusion inevitably leads to missing data; Musculoskeletal forces and moments exerted over the joints from muscles cannot be directly obtained from the sensors [60]; some input channels are not enabled (e.g., partial control) for users with mobility-based chronic conditions (i.e., partial control). In the implementation of VIGOR, Kalman filtering, inverse dynamics, and time-series prediction are employed to handle the incomplete data [35, 61].
The measurement-induced noise is significant.
Figure 5 shows the flowchart of data preprocessing of VIGOR [36, 41, 62, 63]. θv→, where θ is the rotation angle about axis v→, indicates a joint’s Quaternion rotation; xyz denotes a joint’s position; ft indicates a joint’s applied force, which is derived from inverse dynamics; αβγ indicates a joint’s rotation under normalized Joint Coordinate System (JCS) – Euler angle. Its main implementation techniques include data fusion, inverse dynamics analysis, spatial normalization, Kalman filtering, and reconstruction of disable input channels. The kinetic data is stored in JSON format.
Figure 5.
Flowchart of VIGOR’s Preprocessing for kinetic movement identification.
3.1.1 Formulating musculoskeletal kinetic features
Inverse dynamics analysis (IDA), which is derived from Newton-Euler Equations [60, 64, 65, 66, 67, 68], aims to calculate unknown kinetic information (the net joint forces and moments) from measured kinematic information (e.g., position, velocities and accelerations of joints) and measured kinetic information (e.g., ground reaction forces). As illustrated in Figure 5, given joint locations xiyizi, Euler rotation αiβiγi where i denotes the identity of a joint, and ground-reaction force F, the joint force fi and other musculoskeletal kinetic features can be computed via IDA.
As illustrated in Figure 5, VIGOR employs inverse dynamics to compute internal joint forces and moments with given ground reaction forces. Inverse dynamics is implemented by dividing the human body into multiple connected rigid bodies [69, 70], which correspond to relevant anatomical segments such as the thigh, calf, foot, arm, etc. The model’s anthropometric properties (e.g., the mass and moment of inertia) are derived from statistical analysis. In addition, it is assumed that each joint is rotationally frictionless. The proposed methods in Figure 5 can be customized to investigate the biomechanical response of human motion by considering different health issues such as cerebral palsy, poliomyelitis, spinal cord injury, and muscular dystrophy [67].
3.1.2 Spatial normalization
As addressed in Section 2, we can acquire joint positions and rotations, which are denoted as xyz and θv→ respectively. Both need to be normalized to ease and boost the gesture recognition: (1) Normalization of Joint Rotations through the interchangeable conversion among quaternion θv→, Euler angle α, β, γ, and joint positions xyz [71]. (2) Normalization of Joint Positions using bone scaling [61], axis-oriented rotating of view angle, origin translating (which makes a user positioned at the center of a sensor), re-constructing xyz according to joint rotation [49], and polishing the kinetic curve using a Savitzky–Golay filter. Our preliminary experimental results demonstrate that the normalization techniques addressed above can greatly improve the quality of data (less noise and smoother kinetic performance) so as to achieve higher recognition [36, 41, 61].
3.1.3 Recovering occlusion-induced missing data
During sensory data acquisition, unavoidable occlusion may introduce missing data or lost-tracking. VIGOR employs spherical linear interpolation (SLERP) to fix the issues caused by short-term occlusion [35], and employs Kalman filter [72, 73, 74] to fix the missing information (including both position and rotation) caused by long-term occlusion. A preliminary comparison between the raw and preprocessed physical rehabilitation kinematic data is available on our online video [62, 63].
3.1.4 Normalization of the kinetics of users with limited mobility
In order to recognize the kinetic movement of users with disabilities, VIGOR normalizes their kinetic data by compensating the missing data incurred by disabled input channels: in the event that several input channels are disabled, the VIGOR model is able to construct the void input channels by taking the advantage of correlation among all inputs. Compensation can normalize the input data so that VIGOR can achieve higher recognition rate, and its psychological and physiological benefits to users are also under our investigation. Figure 6 demonstrates the application of deep neural network [37, 75] on compensating the missing channels introduced by limited mobility. As our preliminary contribution, multilayer perceptron (MLP), temporal convolutional neural network (tCNN) [46], and autoencoder methods are employed to construct disabled legs and the resulted recognition accuracy is improved [20].
Figure 6.
Normalizing the kinetics of user with limited mobility: (a) Compensation of disabled input channels via Deep Neural Network; (b) tCNN-enabled compensated kinetic status of a wheel-chaired user, who receives “virtual functional legs” (in yellow color).
3.2 Entropy-oriented scoring of human motion
The proposed research employs entropy [76] to grade a user’s movement behavior, which is defined as a times series of joint kinetic features such as positions and rotations. The distance/dissimilarity between two time series can be measured in time-domain or frequency-domain [58, 59]. In time-domain, Approximate Entropy (AppEn) and Sample Entropy (SampEn) [76, 77] can be employed to formulate the regularity and predictability about the normalized Euclidean distance between the time-series of users’ and reference data.
As our preliminary work, Figure 7 compares the entropy values of an advanced Tai-Chi user and a beginner. The whole Tai-Chi set is divided into multiple sub-sequence (or clip), which consists of 25 to 100 frames, and the comparison is made clip-by-clip. In Figure 7, each subsequence consists of 25 frames. It is observed that an advanced Tai-Chi user has smaller entropy than a beginner. Besides the overall entropy of a user, VIGOR also provides the entropy of each joint so that the virtual Tai-Chi coach can provide accurate instruction to users.
Figure 7.
AppEn and SampEn for 25 joints: Comparison of an advanced users and beginner (Each subsequence consists of 25 frames): beginner has larger entropy.
Entropy or cross-entropy analysis can be performed for the time-series in the frequency domain which is derived from discrete Fourier transformation (DFT) or discrete wavelet transformation (DWT) [58, 59]. A hybrid metric that combines both time-domain and frequency-domain information may be considered as well.
3.3 Human motion identification based on machine learning
Many model construction techniques have been developed for time series recognition [59, 78, 79], including K-Nearest-Neighbor (KNN) [80], Support Vector Machines (SVMs) [81, 82], neural networks, decision trees [83, 84], Bayesian networks, the Hidden Markov model (HMM), LSTM-RNN, etc.
In this work, the recognition accuracy of the aforementioned classifiers with respect to three benchmark datasets was determined: Dataset I: UTD Multimodal Human Action Dataset (UTD MHAD [85]), Dataset II: UTKinect-Action3D [86], and Dataset III: Tai-Chi Yang-Style 24 movement [22, 41] (an in-house Kinect skeletal dataset collected for Tai-Chi training). The experimental results showed that SVM and LSTM-RNN surpasses the other classifiers; particularly, LSTM-RNN has a superior recognition accuracy in case of limited number of training data (e.g., 200 training samples). However, LSTM-RNN suffers from unsatisfactory time performance [35]. Scalable algorithms for temporal neural network such as LSTM-RNN and temporal convolutional network (tCNN) need to be developed [46].
In this work, a musculoskeletal biomechanics guided loss function is used to formulate the objective of kinetics classifier:
Lθ=LfXθy+ϱRθ,E1
where y is the pre-determined movement identity; f (X, θ) is predicting movement identity of kinetics sequence X=(〈xtkytkztkf)tk〉t=t0tm (as defined in Figure 5, t is time step ranging from t0 through tm, k is joint’s identity); θ∈ℜn indicates the parameters (weight and bias) of neural network; Rθ:ℜn→ℜ is the regularizer, whose importance is controlled by regularization strength ϱ∈ℜ; and Lθ:ℜn→ℜ is actually regularized loss. The corresponding optimization method is called batch optimizer.
3.4 Reconstruction of 4D instruction/feedback for users
VIGOR can be also regarded as a real-time coaching system to help users improve their physical rehabilitation movement for optimal clinical effect. According to the measure and recognition result discussed above, VTCS generates real-time 4D instructions or guidance to users over virtual reality or augmented reality (AR) platform, as shown in the online video [22, 87, 88] addressed in our preliminary work.
4. Adaptive virtual limb generation
To relieve the physical and psychological suffering of people with limited mobility, VIGOR develops an adaptive (versatile to various types of disability) and full-body-driven virtual limb generation system (all measurable body-parts will be used to formulate virtual limbs). The related technical contributions include: (1) According to specified kinetic script (e.g., dancing, running, etc.) and users’ physical conditions, a hierarchical network is extracted from human musculoskeletal network, which is fabricated by multiple body components (e.g., muscles, bones, and joints, etc.) that are biomechanically, functionally, or neurally correlated with each other and exhibit mostly non-divergent kinetic behaviors. (2) The generated limb can be reconstructed over the VR/AR system, tactile actuator system, and motoring system.
4.1 Pipeline of adaptive virtual limb generation
The proposed work employs deep learning techniques such as autoencoder to generate virtual limbs [89] according to the observed kinetic behaviors of other body parts based on the following hypothesis: (1) The human body consists of multiple components such as muscles, bones, and joints, which are correlated with each other mechanically, neurally, and/or functionally. (2) Deep learning techniques such as autoencoder can be used to capture the kinetic pattern of human movement.
Figure 8(a) shows the flowchart of the adaptive virtual limb generation, which consists of the following critical aspects: (1) Formulating human musculoskeletal network [91] according to the functional, mechanical and neural correlation between each body component (muscle, joint, or bone). (2) Deriving hierarchical network (in the configuration of forest data structure) from the human musculoskeletal network according to the physical status of users, where the virtual limbs will form the leaves of a hierarchical tree. (3) Building visible autoencoder neural network according to the hierarchical network so that the kinetic behavior can be constructed according to the kinetic behavior of user’s functional body parts measured by heterogeneous sensors. (4) Training the addressed visible autoencoder neural network according to specific human movement script such as walking, jogging, dancing, or any other physical activity. (5) Representing kinematic behavior about virtual limbs using VR/AR, tactile actuators, and active orthoses, which can directly stimulate users. Figure 8(b) shows the screenshot of virtual limb generation.
Figure 8.
(a) The flowchart of the proposed adaptive virtual limb generation based on multi-correlation hierarchical autoencoder; (b) Snapshot of virtual limb generation – walking by moving arms (online video [90]).
4.2 Multivariate time series-based kinetics generation of Virtual Limbs
Adaptive and full-body-driven virtual limb generation can (1) engage various individuals with limited mobility in regular physical activities, (2) accelerate the rehabilitation of patients, and (3) release users’ phantom limb pain.
Virtual limb generation is a generative time series problem. Figure 9 shows the pipeline of kinetics generation (a multivariate time-series) and correction of kinetic sequence of the virtual limbs.
Ytmeasured={(xtiytiztif)ti}t=t0tm denotes the measured kinetic sequence of functional body parts. As defined in Figure 5, t is time step ranging from t0 through tm, k is the identity of joints that are related to function body parts.
Ytvirtual={(xtjytjztjf)tj}t=t0tm denotes the generated kinetic sequence of virtual limbs, t is time step ranging from t0 through tm, j is the identity of joints that are related to virtual limbs.
Figure 9.
Generation and correction of the kinetics of virtual limbs.
As illustrated in Figure 6, we can generate the the kinetics of the wheel-chaired Tai-Chi practitioner according to the movement of his/her arms, which are functional and healthy. This work employs deep neural network to generate Ytvirtual using Ytmeasured:
Ytvirtual=fYtmeasuredθE2
where fYtmeasuredθ is the output of deep neural network.
4.2.1 Loss function for the Generation of virtual limbs’ kinetics
In this work, a musculoskeletal biomechanics guided loss function is used to formulate the objective of generated virtual limbs’ kinetics:
Lθ=LYvirtualY+ϱRθ+LbiomechanicsYvirtual.E3
In Eq. (3), (Yvirtual,Y) indicates labelled training data; Yvirtual is the expected kinetic of virtual limbs; θ∈ℜn indicates the parameters (weight and bias) of neural network; Rθ:ℜn→ℜ is the regularizer, whose importance is controlled by regularization strength ϱ∈ℜ;LbiomechanicsYvirtual denotes the bio-mechanics violation of generated kinetics with weigh γ∈ℜ and this work uses kinetic imbalance of human body to measure Lbiomechanics; and Lθ:ℜn→ℜ is actually regularized loss.
4.2.2 Correction of generated kinetics using time-series prediction model
The kinetic sequence of virtual limbs does not behave smoothly. This work corrects Ytvirtual using Auto-Regressive Integrated Moving Average (ARIMA) [44] time-series prediction model. ARIMA model is fitted to time series data for pattern recognition and forecasting. The AR part of ARIMA indicates that the evolving variable of interest is regressed on its prior (or historical) values. The MA part indicates that the regression error is actually a linear combination of error terms whose values occurred contemporaneously and at various times in the past. The I (for “integrated”) indicates that the data values have been replaced with the difference between their values and the previous values. ARIMA is defined as:
Ytvirtual∗=c+∑k=1pϕkYt−kvirtual+∑kqψkεt−k+εtE4
where Ytvirtual is the differenced series (it may have been differenced more than once). The “predictors” on the right hand side include both lagged values of Ytvirtual and lagged errors. Eq. (4) is also called ARIMA(p, d, q) model, where p is the order of the autoregressive part; d is the degree of first differencing involved; q is the order of the moving average part.
Any time series may be split into the following components: base Level, trend, seasonality and error. The coefficient of the ARIMA model is determined through autocorrelation [44] and the correlation of the series with its previous values.
4.3 Formulating the kinetics of virtual limbs using the measured kinetics of functional body parts
As described in Eqs. (2) and (4), the generation of virtual limb kinetics consists of two steps: (1) create preliminary kinetics of virtual limbs according to the measured kinetics of functional body parts; and (2) correct the preliminary kinetics using time series prediction models such as ARIMA. This subsection will focus on Step (1) because it faces more technical challenges.
4.3.1 Configuration of network architecture according human anatomy
It is known that any system can be regarded as a hierarchical structure (i.e., system → subsystem → sub-subsystem, ...). As illustrated in Figure 10(a), the human body system can be always divided into sub-components that are mechanically correlated. Inspired by the Bayesian network, we propose a visible and hierarchical neural network (VHNN), which is derived from human anatomy, to accurately formulate a system. As illustrated in Figure 10(b), a sample visible and hierarchical neural network, which is directly derived from the human body system, is employed to specify the musculoskeletal kinematics. The VHNN can be employed in virtual limb generation, 4D kinetic behavior recognition, and individualized Tai-Chi choreography (to be discussed in the remaining sections). Preliminary experimental results demonstrate that VHNN is superior to a classical neural network from the point of view of training speed and stability.
Figure 10.
(a) Hierarchical human anatomy; (b) visible and hierarchical neural network derived from human anatomy.
4.3.2 Example: generating virtual legs based on arm movement using VHNN
A neural network is trained to generate the kinetic status of hip, knees, and feet according to the kinetic status of shoulders, elbows, and arms captured by 4D sensors [90]. As illustrated in Figure 11(a)–(d), four network architectures are investigated in this research: (a) multiple layer perceptron (MLP); (b) denoising autoencoder (a classical autoencoder architecture); (c) visible and hierarchical neural network with two subsystems (VHNN2); and (c) VHNN with four subsystems (VHNN4). It can be observed that VHNN splits the input tensor and then feeds the split tensor into multiple smaller, parallelized autoencoders. Thus, data for each joint can be calculated in parallel with their own respective autoencoder. The aforementioned parallelized autoencoder pipelines are simplified stacked autoencoders, allowing for optimization of specific, key tasks rather than one large task. A video playlist of the generation of virtual legs based on VHNN may be found at [92].
Figure 11.
Generation of virtual legs from moving arms using various architecture: (a) MLP; (b) denoising autoencoder (a classical architecture); (c) two thread (subsystem) visible and hierarchical autoencoder neural network (VHNN-AE-2); (d) four-thread VHNN (VHNN-AE-4) (notes: LL-LA indicates virtual left-leg induced by left-arm; LL-RA indicates virtual right-leg induced by right arm) (online video: [92]).
As illustrated in Figure 9, the generated kinetics of virtual limbs can be corrected using time-series models such as ARIMA.
As illustrated in Table 1, the proposed VPNN architecture has proven to have overall superior results compared to previous work. Decreased training time compared to previous autoencoders architectures can be observed due to the parallelization of simpler autoencoders, increasing efficiency by easing optimization. This is done by allowing autoencoders to train on specific gestures in a whole movement. In addition, it does not exhibit data-hungry tendencies that state-of-the-art models exhibit, allowing it to be trained on small amounts of data.
Time-performance of virtual-legs generation using visible and hierarchical autoencoder neural network (VHNN), which is derived from human anatomy (Intel Core i9-7900X, 1x NVIDIA GTX1080 Ti, 64GB RAM; MLP does not employ GPU).
Lower ground truth error can be seen in the VPNN-AE-2 versus VPNN-AE-4. This is due to training data having no anomalies that real-time data can exhibit. While VPNN-AE-2 with single-correlation works better when testing against ground truth data, VPNN-AE-4 with double-correlation works better in real-time as the patient may not follow the Tai-Chi movements correctly. This causes worse ground truth error as the added complexity of the architecture increases noise during output, but enables better patient-error tolerance. Because of this additional noise produced of VPNN-AE-4, improvements through larger training datasets, more sophisticated pre- and post-processing of data, as well as improved NN architecture could be achieved.
4.4 Construction of virtual limb using active orthosis
In order to provide users with physical support, the generated virtual limb can be re-constructed on motoring system to drive Hip–knee–ankle–foot orthoses (HKAFOs) [97, 98]. Paralysis of hip abductor muscles is one of the most common reasons for prescribing HKAFOs. They can incorporate flexion–extension and abduction–adduction control and have free or locking joints [99]. Different from passive and semi-active orthoses, the HKAFOs have basically built-in power supplies, one or more actuators for moving the joint, the sensors for getting feedback data [97].
The designed active orthosis is shown in Figure 12(A). Knee and ankle are considered rigid; but with locking mechanisms located at the hip and knee joints, and these parts can move anytime person desires. Therefore, in consequence of any adverse motion, the limb will be protected from harm. Also, in the active orthosis, the system acts from the hip zone and only performs “flexion” and “extension” motions. The HKAFO has two mechanical structures: (1) the gear and T type deflector reducer mechanism to transmit the generated torques of an actuator to the hip joints; and (2) pulley and four-bar mechanism, which is used for transferring the generated torque to the knee joints. With the mechanical system used for the motor to move in both directions, also provided power save, it is being aimed to reduce battery consumption to minimum which was a huge problem in these devices. Illustration of the control circuit is shown in Figure 12(B). The patient’s intention to perform a flexion or extension motion is detected by both EMG and accelerometer sensors. In order to determine the last location of the patient after movement, physical feedback is utilized from the mechanical system. Adding the new ankle joint to HKAFOs for real-time virtual limb can also be considered.
The EMG signals may be subject to preprocessing to remove unwanted interference; the most common sources of interference are power line harmonics and motion artifact from electrode movement. As myoelectric signals have a time sequence with a random number of elements, it is not practical for classification. Therefore, the signal sequence should be mapped to feature vectors. Feature vectors of EMG signals are classified to detect which movement produces specific results. Deep neural networks, fuzzy logic, finite state machine and support vector machine, etc. may be adopted as classifiers. In this work, the Finite State Machine (FSM) was chosen as a classifier. The FSM consists of a status set, input, output, event set, and state transition functions. The behavior of each system’s state is characterized by a possible system state. Here, the transitions between output states are provided, depending on the input variable and the present state of the system. The EMG signals and the accelerometer data collected from both legs are classified using the FSM method. The result of this classification is used for three different situations for actuator input. These situations are: the patient stops, moves right leg or moves left leg, respectively.
Figure 12.
Hip-knee-ankle-foot-orthosis (HKAFO): (A) system configuration, with T-type deflector reducer; (B) control circuit (online video: [98]).
5. Individualized movement choreography
Different users have different health statuses and clinical requirements. VIGOR employs generative deep neural network architecture to create initiative and individualized Tai-Chi movements [26] to benefit users in the most effective way [100, 101, 102]. The most challenging issue in deep learning enabled choreography is how to balance the training reliability and the creativity of neural network. In this work, we propose the following techniques: (1) visible neural network, which incorporates biomechanics into the neural network, is employed to formulate the generative movement; (2) only mechanical property such as joint/muscle force and moment is used to measure the generative movement; (3) second-order optimizer is used to speed up the training the neural network.
5.1 Tai-Chi choreography based on LSTM-RNN
In this work, Long Short-Term Memory type of RNN (denoted as LSTM) [103, 104] is employed to design individualized Tai-Chi choreography [26]. Human3.6M dataset (high quality 3D joint positions and rotations at 50FPS) and our in-house dataset (acquired by Microsoft Kinect V2, including joints’ XYZ and Quaternions, 24-30FPS) are used as the training data. The Tai-Chi movement is created clip by clip (or subsequence by subsequence) according to users’ health conditions and their clinical rehabilitation requirements [20].
Figure 13 shows the frame-work of LSTM-based Tai-Chi choreography design. A Tai-Chi movement (or sequence) is partitioned into multiple subsequences (aka a clip or clips). A seed subsequence, which can be generated randomly, is fed into the trained model. The output token is regarded as the succeeding subsequence that is fed back into the model for the following subsequence, as a result a creative Tai-Chi sequence can be created clip-by-clip. Four thread visible and hierarchical AutoEncoders [106] are used to reduce problem dimensionality. The resulting individualized Tai-Chi choreography [100, 101, 102] is integrated into the VR or AR environment [88] from which users can learn. Online video [105] shows a sample Tai-Chi choreography. Compared to other deep learning-enabled choreography projects [107], the proposed method may have faster training speed and be more problem-oriented because (1) the geometric configuration of human anatomy is kept by employing Joint-coordinate systems such as Euler angles. [36, 41], and (2) human biomechanics are preserved by introducing kinetic features [41, 108].
Figure 13.
The pipeline of LSTM-based motion chorepgraphy (online video of LSTM-based Tai-Chi Choreography [88, 105]).
5.2 Movement choreography based on visible GAN
LSTM-based choreography suffers from relatively large accumulated error and lacks a global picture of Tai-Chi choreography. As an effective deep generative model, Generative Adversarial Networks (GANs) learn to model distribution either with or without supervision for high dimensional data (images, texts, audios, etc.), and have been gaining considerable attention in many fields [109, 110, 111]. In VIGOR, GANs may be considered to generate novel Tai-Chi movements by simulating a given distribution.
As illustrated in this work, conventional GAN such as DCAN [46], suffers from frequent modal collapse during the training state, particularly on generator side. The discriminator often improves too quickly for the generator to catch up, which is why we need to regulate the learning rates or perform multiple epochs on one of the two networks. To balance the training of generator and discriminator for decent output, this work investigates the following strategies: (1) Application of Wasserstein distance to formulate the loss function [46, 112]. (2) Application of visible neural network by incorporating the biomechanics theory (inverse dynamics and the transient dynamics simulation of human body [60, 68]) in the formulation of generator and discriminator. The neural network is personalized using boundary and initial conditions of human dynamics.
Figure 14 shows the pipeline of GAN-enabled human movement choreography system. A generator G generates kinematic data out of latent vector, and a discriminator D estimates the probability that a sample came from the training data rather than G. Fed with latent vector, which is randomly generated in the beginning and derived from the transient dynamics simulation of human body thereafter, the generator generates a series of personalized and creative Tai-Chi kinetic subsequence to fool the discriminator. The discriminator is trained to discriminate between “real” Tai-Chi kinetic sub-sequences (from the training set) and “fake” Tai-Chi sub-sequence generated by the generator. Because the generator is fed with deterministic simulated data, an equilibrium of the “adversarial game” between the generator and discriminator can be reached much easily.
Figure 14.
Movement choreography enabled by visible GAN.
In this work, a musculoskeletal biomechanics guided loss function is used to formulate the objective of discriminator:
Lθ=LfXθY+ϱRθ+γLbiomechanicsfXθ+ηLaestheticsfXθE5
where {X,Y} indicates labelled training data; f (X, θ) is predicting output of neural network; θ∈ℜn indicates the parameters (weight and bias) of neural network; Rθ:ℜn→ℜ is the regularizer, whose importance is controlled by regularization strength ϱ∈ℜ; same as Eq. (3), Lbiomechanics(f (X, θ)) denotes the bio-mechanics violation of choreography with weigh γ∈ℜ; Laesthetics(f (X, θ)) denotes the violation of athletic elegance violation about the designed choreography with weigh η∈ℜ.
Figure 14 also illustrates that the generated kinetics needs to made temporally consistent according to specific time series prediction models such as ARIMA (Eq. (4)), LSTM, and Fast Fourier Transformation (FFT).
Many deep-learning-enabled applications suffer from training data scarcity. Various strategies have been investigated to overcome this limitation. Besides visible neural network, polynomial-based Hessian-free Newton-Raphson algorithm (poly-HFNR) [69, 113] is proposed to deal with data scarcity issue by speeding up the NN learning efficiency. The superiority of poly-HFNR optimizers includes: (1) A fewer number of training epochs in NN configuration than first-order-convergence optimizers such as stochastic gradient decent (SGD) algorithms; (2) Less computation and storage complexity (O(N) where N is the degree-of-freedom of neural network) than typical implementation of Newton-Raphson based algorithms; (3) Non-convex tolerance; and (4) Circumventing the explicit formulation of the Hessian matrix and the iterative/direct solution to Newton’s equations (for optimization) during the training process of the neural network.
Poly-HFNR based on Neumann-series-based (Neumann-poly-HFNR) and poly-HFNR based on generalized least-squared polynomial (GLS-poly-HFNR) [47, 69, 113, 114] have been developed and critically assessed with respect to benchmark problems such as iris-classification, air-foil recognition, simulation of yacht-dynamics, and pima Indian diabetes. Both implementations demonstrate reliable and super-linear convergence performance. The experimental results illustrate that: (1) from the point of view of storage and computation complexity, poly-HFNR is comparable with SGD; (2) from the point of view of convergence performance, poly-HFNR is completely comparable with Quasi-Newton. Our future work will focus on (a) evaluating poly-HFNR on various large-scale benchmark problems; (b) improving the convergence of poly-HFNR from super-linear to quadratic convergence rate; and (c) developing CUDA-version poly-HFNR and then transplanting it into popular deep learning framework such as Pytorch, TensorFlow, and Caffe.
6. Conclusion
This work presents VIGOR system that has a strong potential for broad significance to the physical and psychological health of people with limited mobility. It is expected that VIGOR may (1) produce an affordable and user-friendly platform which promotes regular physical activity via a seamless interaction between the user and the Tai-Chi model/master; (2) cultivate and enhance interdisciplinary research by integrating the expertise of physical therapy, psychology, computer science, electrical engineering, and structural mechanics; and (3) adapt to other movement modalities (e.g, yoga).
The major research elements include: (1) Seamless real-time 4D human-machine interaction based on affordable input/output hardware instruments such as Kinect sensor, foot-pressure sensors, actuator, assistive device/exoskeleton, and VR goggle, etc.; (2) Kinetic movement grading and identification; (3) Adaptive virtual limb generation over VR/AR and assistive device/exoskeketon; and (4) Individualized movement choreography(i.e., creative movement design). As the major research contributions of this work, visible and hierarchical neural network (VHNN) architecture is proposed to recognize and predict human kinetics efficiently; and a polynomial-based, Newton-Raphson algorithm is proposed for efficient optimization. Both techniques play significant roles in small-data problems.
As part of our future work, the clinical effect of VIGOR system will be assessed. Specifically, we plan to evaluate both the user-experience and the feasibility of VIGOR by conducting a few of phases of a human subject study with healthy and mobility-limited adult human subjects. In every phase, subjects will be surveyed and interviewed following exposure to VIGOR. The clinical data will be analyzed using Auto-Regressive Integrated Moving Average (ARIMA) model [44].
Acknowledgments
This work was jointly sponsored by National Science Foundation (NSF) 1924278, 1761839 and 1647175.
\n',keywords:"deep learning, 4D experience, virtual reality, kinetics, active orthosis, physical inactivity",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/75808.pdf",chapterXML:"https://mts.intechopen.com/source/xml/75808.xml",downloadPdfUrl:"/chapter/pdf-download/75808",previewPdfUrl:"/chapter/pdf-preview/75808",totalDownloads:221,totalViews:0,totalCrossrefCites:0,dateSubmitted:null,dateReviewed:"January 15th 2021",datePrePublished:"April 7th 2021",datePublished:"January 12th 2022",dateFinished:"March 19th 2021",readingETA:"0",abstract:"Physical inactivity is a major national concern, particularly among individuals with chronic conditions and/or disabilities. There is an urgent need to devise practical and innovative fitness methods, designed and grounded in physical, psychological and social considerations that will effectively promote physical fitness participation among individuals of all age groups with chronic health condition(s) and/or disabilities. This research is dedicated to achieving Versatile, Individualized, and Generative ORchestrator (VIGOR) to motivate the movement of the people with limited mobility. Tai-Chi is a traditional mind–body wellness and healing art, and its clinical benefits have been well documented. This work presents a Tai-Chi based VIGOR under development. Through the use of Helping, Pushing and Coaching (HPC) functions by following Tai-Chi kinematics, the VIGOR system is designed to make engagement in physical activity an affordable, individually engaging, and enjoyable experience for individuals who live with mobility due to disease or injury. VIGOR consists of the following major modules: (1) seamless human-machine interaction based on the acquisition, transmission, and reconstruction of 4D data (XYZ plus somatosensory) using affordable I/O instruments such as Kinect, Sensor and Tactile actuator, and active-orthosis/exoskeleton; (2) processing and normalization of kinetic data; (3) Identification and grading of kinetics in real time; (4) adaptive virtual limb generation and its reconstruction on virtual reality (VR) or active-orthosis/exoskeleton; and (5) individualized physical activity choreography (i.e., creative movement design). Aiming at developing a deep-learning-enabled rehab and fitness modality through infusing the domain knowledge (physical therapy, medical anthropology, psychology, electrical engineering, bio-mechanics, and athletic aesthetics) into deep neural network, this work is transformative in that the technology can be applied to the broad research areas of intelligent systems, human-computer interaction, and cyber-physical human systems. The resulting VIGOR has significant potentials as both rehabilitative and fitness modalities and can be adapted to other movement modalities and chronic medical conditions (e.g., yoga and balance exercise; fibromyalgia, multiple sclerosis, Parkinson disease).",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/75808",risUrl:"/chapter/ris/75808",signatures:"Yu Liang, Dalei Wu, Dakila Ledesma, Zibin Guo, Erkan Kaplanoglu and Anthony Skjellum",book:{id:"10298",type:"book",title:"Smart and Pervasive Healthcare",subtitle:null,fullTitle:"Smart and Pervasive Healthcare",slug:"smart-and-pervasive-healthcare",publishedDate:"January 12th 2022",bookSignature:"Urvashi Sharma",coverURL:"https://cdn.intechopen.com/books/images_new/10298.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83968-681-8",printIsbn:"978-1-83968-680-1",pdfIsbn:"978-1-83968-682-5",isAvailableForWebshopOrdering:!0,editors:[{id:"105398",title:"Dr.",name:"Urvashi",middleName:null,surname:"Sharma",slug:"urvashi-sharma",fullName:"Urvashi Sharma"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"332945",title:"Prof.",name:"Yu",middleName:null,surname:"Liang",fullName:"Yu Liang",slug:"yu-liang",email:"yu-liang@utc.edu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/332945/images/14606_n.jpg",institution:{name:"University of Tennessee at Chattanooga",institutionURL:null,country:{name:"United States of America"}}},{id:"336952",title:"Dr.",name:"Dalei",middleName:null,surname:"Wu",fullName:"Dalei Wu",slug:"dalei-wu",email:"dalei-wu@utc.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Tennessee at Chattanooga",institutionURL:null,country:{name:"United States of America"}}},{id:"336953",title:"Dr.",name:"Zibin-",middleName:null,surname:"Guo",fullName:"Zibin- Guo",slug:"zibin-guo",email:"zibin-guo@utc.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Tennessee at Chattanooga",institutionURL:null,country:{name:"United States of America"}}},{id:"336955",title:"Mr.",name:"Dakila",middleName:null,surname:"Ledesma",fullName:"Dakila Ledesma",slug:"dakila-ledesma",email:"BGQ527@mocs.utc.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Tennessee at Chattanooga",institutionURL:null,country:{name:"United States of America"}}},{id:"337918",title:"Dr.",name:"Erkan",middleName:null,surname:"Kaplanoglu",fullName:"Erkan Kaplanoglu",slug:"erkan-kaplanoglu",email:"erkan-kaplanoglu@utc.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Tennessee at Chattanooga",institutionURL:null,country:{name:"United States of America"}}},{id:"337919",title:"Dr.",name:"Anthony",middleName:null,surname:"Skjellum",fullName:"Anthony Skjellum",slug:"anthony-skjellum",email:"Tony-Skjellum@utc.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Tennessee at Chattanooga",institutionURL:null,country:{name:"United States of America"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_1_2",title:"1.1 Motivation",level:"2"},{id:"sec_2_2",title:"1.2 Rationale for the VIGOR system to address aging and chronic disability",level:"2"},{id:"sec_3_2",title:"1.3 VIGOR’s infrastructure",level:"2"},{id:"sec_4_2",title:"1.4 Research objectives and function modules of VIGOR",level:"2"},{id:"sec_6",title:"2. Real-time 4D human-machine interaction",level:"1"},{id:"sec_6_2",title:"2.1 Acquisition of 4D sensory data",level:"2"},{id:"sec_6_3",title:"2.1.1 Acquisition and processing of kinematic data",level:"3"},{id:"sec_7_3",title:"2.1.2 Acquisition of tactile data",level:"3"},{id:"sec_9_2",title:"2.2 Reconstruction of 4D data",level:"2"},{id:"sec_10_2",title:"2.3 Developing communication and edge-computing protocols",level:"2"},{id:"sec_10_3",title:"2.3.1 Real-time, two-way communication",level:"3"},{id:"sec_11_3",title:"2.3.2 Deployment of VIGOR on affordable hardware using edge computing",level:"3"},{id:"sec_14",title:"3. Identification and scoring of user’s kinetic movement",level:"1"},{id:"sec_14_2",title:"3.1 Preprocessing pipeline for kinetic movement identification",level:"2"},{id:"sec_14_3",title:"3.1.1 Formulating musculoskeletal kinetic features",level:"3"},{id:"sec_15_3",title:"3.1.2 Spatial normalization",level:"3"},{id:"sec_16_3",title:"3.1.3 Recovering occlusion-induced missing data",level:"3"},{id:"sec_17_3",title:"3.1.4 Normalization of the kinetics of users with limited mobility",level:"3"},{id:"sec_19_2",title:"3.2 Entropy-oriented scoring of human motion",level:"2"},{id:"sec_20_2",title:"3.3 Human motion identification based on machine learning",level:"2"},{id:"sec_21_2",title:"3.4 Reconstruction of 4D instruction/feedback for users",level:"2"},{id:"sec_23",title:"4. Adaptive virtual limb generation",level:"1"},{id:"sec_23_2",title:"4.1 Pipeline of adaptive virtual limb generation",level:"2"},{id:"sec_24_2",title:"4.2 Multivariate time series-based kinetics generation of Virtual Limbs",level:"2"},{id:"sec_24_3",title:"4.2.1 Loss function for the Generation of virtual limbs’ kinetics",level:"3"},{id:"sec_25_3",title:"4.2.2 Correction of generated kinetics using time-series prediction model",level:"3"},{id:"sec_27_2",title:"4.3 Formulating the kinetics of virtual limbs using the measured kinetics of functional body parts",level:"2"},{id:"sec_27_3",title:"4.3.1 Configuration of network architecture according human anatomy",level:"3"},{id:"sec_28_3",title:"Table 1.",level:"3"},{id:"sec_30_2",title:"4.4 Construction of virtual limb using active orthosis",level:"2"},{id:"sec_32",title:"5. Individualized movement choreography",level:"1"},{id:"sec_32_2",title:"5.1 Tai-Chi choreography based on LSTM-RNN",level:"2"},{id:"sec_33_2",title:"5.2 Movement choreography based on visible GAN",level:"2"},{id:"sec_34_2",title:"5.3 Polynomial-based Hessian-free Newton–Raphson optimizer",level:"2"},{id:"sec_36",title:"6. Conclusion",level:"1"},{id:"sec_37",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Marini, I., and Stebnicki, M. A. The Psychological and Social Impact of Illness and Disability, 6th Ed. Springer publishing, 2012'},{id:"B2",body:'[report] physical inactivity among adults 50 years and older - united states, 2014. Morbidity and Mortality Weekly Report 2016 65, 36 (2016)'},{id:"B3",body:'Kelley, G., Kelley, K., Hootman, J., and Jones, D. Effects of community-deliverable exercise on pain and physical function in adults with arthritis and other rheumatic diseases: a meta-analysis. Arthritis Care Res. 63, 1 (2011), 79–93'},{id:"B4",body:'Fasko, D. 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[online] active hip-knee-ankle-foot orthosis (a-hkafo). https://www.youtube.com/watch?v=JbFSDunV8Js. Cite September 20, 2019'},{id:"B99",body:'Webster, J. B., and Murphy, D. P. Atlas of Orthoses and Assistive Devices (Fifth Edition). 2019'},{id:"B100",body:'Berman, A., and James, V. Kinetic imaginations: Exploring the possibilities of combining ai and dance. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015) (Buenos Aires, Argentina, 25–31 July 2015), pp. 2431–2437'},{id:"B101",body:'Briot, J.-P., Hadjeres, G., and Pachet, F. Deep learning techniques for music generation – a survey. arXiv:1709.01620 (2018), 1–108'},{id:"B102",body:'Donahue, C., Lipton, Z. C., and McAuley, J. Dance dance convolution. CoRR abs/1703.06891 (2017)'},{id:"B103",body:'Hammer, B. Learning with Recurrent Neural Networks. Springer, October 2007'},{id:"B104",body:'Hochreiter, S., and Schmidhuber, J. Long short-term memory. Neural Computation 9, 8 (1997), 1735–1780'},{id:"B105",body:'Liang, Y., and Ledesma, D. [online] vtcs: Tai-chi choreography derived from lstm-rnn. https://youtu.be/phcncKvq4hQ. cite June 18, 2018'},{id:"B106",body:'Géron, A. Hands-On Machine Learning with Scikit-Learn and TensorFlow. O’Reilly, 2017'},{id:"B107",body:'Crnkovic-Friis, L., and Crnkovic-Friis, L. Generative choreography using deep learning. ICCC (2016)'},{id:"B108",body:'Yuan, X., Kong, L., Feng, D., and Wei, Z. Automatic feature point detection and tracking of human action in time-of-flight videos. IEEE/CAA Journal of Automatica Sinica 4, 4 (Oct. 2017), 677–685'},{id:"B109",body:'Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xü, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y. Generative adversarial nets. In Proc. of Advances in Neural Information Processing Systems (2014)'},{id:"B110",body:'Elgammal, A., Liu, B., Elhoseiny, M., and Mazzone, M. Can: Creative adversarial networks generating “art” by learning about styles and deviating from style norms. arXiv:1706.07068 6 (2017), 1–22'},{id:"B111",body:'Hong, Y., Hwang, U., Yoo, J., and Yoon, S. How generative adversarial networks and their variants work: An overview of gan. arXiv:1711.05914v7, July 2018'},{id:"B112",body:'Endres, D. M., and Schindelin, J. E. A new metric for probability distributions. IEEE Transactions on Information Theory 49, 7 (July 2003), 1858–1860'},{id:"B113",body:'Liang, Y., Shi, Z., and Chung, P. A hessian-free newton-raphson method for the configuration of physics systems featured by numerically asymmetric force field. Mathematical and Computer Simulation (February 2017), 1–23'},{id:"B114",body:'Liang, Y., Weston, J., and Szularz, M. Generalized least-squares polynomial preconditioners for symmetric indefinite linear equations. Parallel computing (Impact Factor: 1.693) 28, 2 (2002), 323–341'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Yu Liang",address:"yu-liang@utc.edu",affiliation:'
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UK Research and Innovation (former Research Councils UK (RCUK) - including AHRC, BBSRC, ESRC, EPSRC, MRC, NERC, STFC.) Processing charges for books/book chapters can be covered through RCUK block grants which are allocated to most universities in the UK, which then handle the OA publication funding requests. It is at the discretion of the university whether it will approve the request.)
UK Research and Innovation (former Research Councils UK (RCUK) - including AHRC, BBSRC, ESRC, EPSRC, MRC, NERC, STFC.) Processing charges for books/book chapters can be covered through RCUK block grants which are allocated to most universities in the UK, which then handle the OA publication funding requests. It is at the discretion of the university whether it will approve the request.)
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Her research interest is radiology and neuroscience technology and application. She had been trained as an imaging scientist at several prestigious institutes including Columbia University, the University of Pennsylvania, and the National Institutes of Health (NIH). Her research focuses on multi-modal neuroimaging integration such as MRI/PET and EEG/MEG instrumentation to make the best use of multiple modalities for better interpretation of underlying disease mechanisms. She is the author and editor of more than twelve books for well-known publishers including IntechOpen and Nova Science. She has published more than 100 papers and abstracts in many reputed international journals and conferences and served as reviewer and editor for several academic associations.",institutionString:"University of Southern California",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"4",institution:{name:"University of Southern California",institutionURL:null,country:{name:"United States of America"}}},equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9629",title:"Electroencephalography",subtitle:"From Basic Research to Clinical Applications",isOpenForSubmission:!1,hash:"8147834b6c6deeeec40f407c71ad60b4",slug:"electroencephalography-from-basic-research-to-clinical-applications",bookSignature:"Hideki Nakano",coverURL:"https://cdn.intechopen.com/books/images_new/9629.jpg",editedByType:"Edited 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by"}}],booksByTopicTotal:65,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"46296",doi:"10.5772/57398",title:"Physiological Role of Amyloid Beta in Neural Cells: The Cellular Trophic Activity",slug:"physiological-role-of-amyloid-beta-in-neural-cells-the-cellular-trophic-activity",totalDownloads:5886,totalCrossrefCites:18,totalDimensionsCites:31,abstract:null,book:{id:"3846",slug:"neurochemistry",title:"Neurochemistry",fullTitle:"Neurochemistry"},signatures:"M. del C. Cárdenas-Aguayo, M. del C. Silva-Lucero, M. Cortes-Ortiz,\nB. Jiménez-Ramos, L. Gómez-Virgilio, G. Ramírez-Rodríguez, E. Vera-\nArroyo, R. Fiorentino-Pérez, U. García, J. Luna-Muñoz and M.A.\nMeraz-Ríos",authors:[{id:"42225",title:"Dr.",name:"Jose",middleName:null,surname:"Luna-Muñoz",slug:"jose-luna-munoz",fullName:"Jose Luna-Muñoz"},{id:"114746",title:"Dr.",name:"Marco",middleName:null,surname:"Meraz-Ríos",slug:"marco-meraz-rios",fullName:"Marco Meraz-Ríos"},{id:"169616",title:"Dr.",name:"Maria del Carmen",middleName:null,surname:"Cardenas-Aguayo",slug:"maria-del-carmen-cardenas-aguayo",fullName:"Maria del Carmen Cardenas-Aguayo"},{id:"169857",title:"Dr.",name:"Maria del Carmen",middleName:null,surname:"Silva-Lucero",slug:"maria-del-carmen-silva-lucero",fullName:"Maria del Carmen Silva-Lucero"},{id:"169858",title:"Dr.",name:"Maribel",middleName:null,surname:"Cortes-Ortiz",slug:"maribel-cortes-ortiz",fullName:"Maribel Cortes-Ortiz"},{id:"169859",title:"Dr.",name:"Berenice",middleName:null,surname:"Jimenez-Ramos",slug:"berenice-jimenez-ramos",fullName:"Berenice Jimenez-Ramos"},{id:"169860",title:"Dr.",name:"Laura",middleName:null,surname:"Gomez-Virgilio",slug:"laura-gomez-virgilio",fullName:"Laura Gomez-Virgilio"},{id:"169861",title:"Dr.",name:"Gerardo",middleName:null,surname:"Ramirez-Rodriguez",slug:"gerardo-ramirez-rodriguez",fullName:"Gerardo Ramirez-Rodriguez"},{id:"169862",title:"Dr.",name:"Eduardo",middleName:null,surname:"Vera-Arroyo",slug:"eduardo-vera-arroyo",fullName:"Eduardo Vera-Arroyo"},{id:"169863",title:"Dr.",name:"Rosana Sofia",middleName:null,surname:"Fiorentino-Perez",slug:"rosana-sofia-fiorentino-perez",fullName:"Rosana Sofia Fiorentino-Perez"},{id:"169864",title:"Dr.",name:"Ubaldo",middleName:null,surname:"Garcia",slug:"ubaldo-garcia",fullName:"Ubaldo Garcia"}]},{id:"58070",doi:"10.5772/intechopen.72427",title:"MRI Medical Image Denoising by Fundamental Filters",slug:"mri-medical-image-denoising-by-fundamental-filters",totalDownloads:2564,totalCrossrefCites:17,totalDimensionsCites:30,abstract:"Nowadays Medical imaging technique Magnetic Resonance Imaging (MRI) plays an important role in medical setting to form high standard images contained in the human brain. MRI is commonly used once treating brain, prostate cancers, ankle and foot. The Magnetic Resonance Imaging (MRI) images are usually liable to suffer from noises such as Gaussian noise, salt and pepper noise and speckle noise. So getting of brain image with accuracy is very extremely task. An accurate brain image is very necessary for further diagnosis process. During this chapter, a median filter algorithm will be modified. Gaussian noise and Salt and pepper noise will be added to MRI image. A proposed Median filter (MF), Adaptive Median filter (AMF) and Adaptive Wiener filter (AWF) will be implemented. The filters will be used to remove the additive noises present in the MRI images. The noise density will be added gradually to MRI image to compare performance of the filters evaluation. The performance of these filters will be compared exploitation the applied mathematics parameter Peak Signal-to-Noise Ratio (PSNR).",book:{id:"6144",slug:"high-resolution-neuroimaging-basic-physical-principles-and-clinical-applications",title:"High-Resolution Neuroimaging",fullTitle:"High-Resolution Neuroimaging - Basic Physical Principles and Clinical Applications"},signatures:"Hanafy M. Ali",authors:[{id:"213318",title:"Dr.",name:"Hanafy",middleName:"M.",surname:"Ali",slug:"hanafy-ali",fullName:"Hanafy Ali"}]},{id:"41589",doi:"10.5772/50323",title:"The Role of the Amygdala in Anxiety Disorders",slug:"the-role-of-the-amygdala-in-anxiety-disorders",totalDownloads:9671,totalCrossrefCites:4,totalDimensionsCites:28,abstract:null,book:{id:"2599",slug:"the-amygdala-a-discrete-multitasking-manager",title:"The Amygdala",fullTitle:"The Amygdala - A Discrete Multitasking Manager"},signatures:"Gina L. Forster, Andrew M. Novick, Jamie L. Scholl and Michael J. Watt",authors:[{id:"145620",title:"Dr.",name:"Gina",middleName:null,surname:"Forster",slug:"gina-forster",fullName:"Gina Forster"},{id:"146553",title:"BSc.",name:"Andrew",middleName:null,surname:"Novick",slug:"andrew-novick",fullName:"Andrew Novick"},{id:"146554",title:"MSc.",name:"Jamie",middleName:null,surname:"Scholl",slug:"jamie-scholl",fullName:"Jamie Scholl"},{id:"146555",title:"Dr.",name:"Michael",middleName:null,surname:"Watt",slug:"michael-watt",fullName:"Michael Watt"}]},{id:"26258",doi:"10.5772/28300",title:"Excitotoxicity and Oxidative Stress in Acute Ischemic Stroke",slug:"excitotoxicity-and-oxidative-stress-in-acute-ischemic-stroke",totalDownloads:7157,totalCrossrefCites:6,totalDimensionsCites:25,abstract:null,book:{id:"931",slug:"acute-ischemic-stroke",title:"Acute Ischemic Stroke",fullTitle:"Acute Ischemic Stroke"},signatures:"Ramón Rama Bretón and Julio César García Rodríguez",authors:[{id:"73430",title:"Prof.",name:"Ramon",middleName:null,surname:"Rama",slug:"ramon-rama",fullName:"Ramon Rama"},{id:"124643",title:"Prof.",name:"Julio Cesar",middleName:null,surname:"García",slug:"julio-cesar-garcia",fullName:"Julio Cesar García"}]},{id:"62072",doi:"10.5772/intechopen.78695",title:"Brain-Computer Interface and Motor Imagery Training: The Role of Visual Feedback and Embodiment",slug:"brain-computer-interface-and-motor-imagery-training-the-role-of-visual-feedback-and-embodiment",totalDownloads:1439,totalCrossrefCites:13,totalDimensionsCites:23,abstract:"Controlling a brain-computer interface (BCI) is a difficult task that requires extensive training. Particularly in the case of motor imagery BCIs, users may need several training sessions before they learn how to generate desired brain activity and reach an acceptable performance. A typical training protocol for such BCIs includes execution of a motor imagery task by the user, followed by presentation of an extending bar or a moving object on a computer screen. In this chapter, we discuss the importance of a visual feedback that resembles human actions, the effect of human factors such as confidence and motivation, and the role of embodiment in the learning process of a motor imagery task. Our results from a series of experiments in which users BCI-operated a humanlike android robot confirm that realistic visual feedback can induce a sense of embodiment, which promotes a significant learning of the motor imagery task in a short amount of time. We review the impact of humanlike visual feedback in optimized modulation of brain activity by the BCI users.",book:{id:"6610",slug:"evolving-bci-therapy-engaging-brain-state-dynamics",title:"Evolving BCI Therapy",fullTitle:"Evolving BCI Therapy - Engaging Brain State Dynamics"},signatures:"Maryam Alimardani, Shuichi Nishio and Hiroshi Ishiguro",authors:[{id:"11981",title:"Prof.",name:"Hiroshi",middleName:null,surname:"Ishiguro",slug:"hiroshi-ishiguro",fullName:"Hiroshi Ishiguro"},{id:"231131",title:"Dr.",name:"Maryam",middleName:null,surname:"Alimardani",slug:"maryam-alimardani",fullName:"Maryam Alimardani"},{id:"231134",title:"Dr.",name:"Shuichi",middleName:null,surname:"Nishio",slug:"shuichi-nishio",fullName:"Shuichi Nishio"}]}],mostDownloadedChaptersLast30Days:[{id:"29764",title:"Underlying Causes of Paresthesia",slug:"underlying-causes-of-paresthesia",totalDownloads:192666,totalCrossrefCites:3,totalDimensionsCites:7,abstract:null,book:{id:"1069",slug:"paresthesia",title:"Paresthesia",fullTitle:"Paresthesia"},signatures:"Mahdi Sharif-Alhoseini, Vafa Rahimi-Movaghar and Alexander R. Vaccaro",authors:[{id:"91165",title:"Prof.",name:"Vafa",middleName:null,surname:"Rahimi-Movaghar",slug:"vafa-rahimi-movaghar",fullName:"Vafa Rahimi-Movaghar"}]},{id:"63258",title:"Anatomy and Function of the Hypothalamus",slug:"anatomy-and-function-of-the-hypothalamus",totalDownloads:4558,totalCrossrefCites:6,totalDimensionsCites:12,abstract:"The hypothalamus is a small but important area of the brain formed by various nucleus and nervous fibers. Through its neuronal connections, it is involved in many complex functions of the organism such as vegetative system control, homeostasis of the organism, thermoregulation, and also in adjusting the emotional behavior. The hypothalamus is involved in different daily activities like eating or drinking, in the control of the body’s temperature and energy maintenance, and in the process of memorizing. It also modulates the endocrine system through its connections with the pituitary gland. Precise anatomical description along with a correct characterization of the component structures is essential for understanding its functions.",book:{id:"6331",slug:"hypothalamus-in-health-and-diseases",title:"Hypothalamus in Health and Diseases",fullTitle:"Hypothalamus in Health and Diseases"},signatures:"Miana Gabriela Pop, Carmen Crivii and Iulian Opincariu",authors:null},{id:"57103",title:"GABA and Glutamate: Their Transmitter Role in the CNS and Pancreatic Islets",slug:"gaba-and-glutamate-their-transmitter-role-in-the-cns-and-pancreatic-islets",totalDownloads:3478,totalCrossrefCites:3,totalDimensionsCites:9,abstract:"Glutamate and gamma-aminobutyric acid (GABA) are the major neurotransmitters in the mammalian brain. Inhibitory GABA and excitatory glutamate work together to control many processes, including the brain’s overall level of excitation. The contributions of GABA and glutamate in extra-neuronal signaling are by far less widely recognized. In this chapter, we first discuss the role of both neurotransmitters during development, emphasizing the importance of the shift from excitatory to inhibitory GABAergic neurotransmission. The second part summarizes the biosynthesis and role of GABA and glutamate in neurotransmission in the mature brain, and major neurological disorders associated with glutamate and GABA receptors and GABA release mechanisms. The final part focuses on extra-neuronal glutamatergic and GABAergic signaling in pancreatic islets of Langerhans, and possible associations with type 1 diabetes mellitus.",book:{id:"6237",slug:"gaba-and-glutamate-new-developments-in-neurotransmission-research",title:"GABA And Glutamate",fullTitle:"GABA And Glutamate - New Developments In Neurotransmission Research"},signatures:"Christiane S. Hampe, Hiroshi Mitoma and Mario Manto",authors:[{id:"210220",title:"Prof.",name:"Christiane",middleName:null,surname:"Hampe",slug:"christiane-hampe",fullName:"Christiane Hampe"},{id:"210485",title:"Prof.",name:"Mario",middleName:null,surname:"Manto",slug:"mario-manto",fullName:"Mario Manto"},{id:"210486",title:"Prof.",name:"Hiroshi",middleName:null,surname:"Mitoma",slug:"hiroshi-mitoma",fullName:"Hiroshi Mitoma"}]},{id:"35802",title:"Cross-Cultural/Linguistic Differences in the Prevalence of Developmental Dyslexia and the Hypothesis of Granularity and Transparency",slug:"cross-cultural-linguistic-differences-in-the-prevalence-of-developmental-dyslexia-and-the-hypothesis",totalDownloads:3601,totalCrossrefCites:2,totalDimensionsCites:7,abstract:null,book:{id:"673",slug:"dyslexia-a-comprehensive-and-international-approach",title:"Dyslexia",fullTitle:"Dyslexia - A Comprehensive and International Approach"},signatures:"Taeko N. Wydell",authors:[{id:"87489",title:"Prof.",name:"Taeko",middleName:"N.",surname:"Wydell",slug:"taeko-wydell",fullName:"Taeko Wydell"}]},{id:"58597",title:"Testosterone and Erectile Function: A Review of Evidence from Basic Research",slug:"testosterone-and-erectile-function-a-review-of-evidence-from-basic-research",totalDownloads:1331,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"Androgens are essential for male physical activity and normal erectile function. Hence, age-related testosterone deficiency, known as late-onset hypogonadism (LOH), is considered a risk factor for erectile dysfunction (ED). This chapter summarizes relevant basic research reports examining the effects of testosterone on erectile function. Testosterone affects several organs and is especially active on the erectile tissue. The mechanism of testosterone deficiency effects on erectile function and the results of testosterone replacement therapy (TRT) have been well studied. Testosterone affects nitric oxide (NO) production and phosphodiesterase type 5 (PDE-5) expression in the corpus cavernosum through molecular pathways, preserves smooth muscle contractility by regulating both contraction and relaxation, and maintains the structure of the corpus cavernosum. Interestingly, testosterone deficiency has relationship to neurological diseases, which leads to ED. Testosterone replacement therapy is widely used to treat patients with testosterone deficiency; however, this treatment might also induce some problems. Basic research suggests that PDE-5 inhibitors, L-citrulline, and/or resveratrol therapy might be effective therapeutic options for testosterone deficiency-induced ED. Future research should confirm these findings through more specific experiments using molecular tools and may shed more light on endocrine-related ED and its possible treatments.",book:{id:"5994",slug:"sex-hormones-in-neurodegenerative-processes-and-diseases",title:"Sex Hormones in Neurodegenerative Processes and Diseases",fullTitle:"Sex Hormones in Neurodegenerative Processes and Diseases"},signatures:"Tomoya Kataoka and Kazunori Kimura",authors:[{id:"219042",title:"Ph.D.",name:"Tomoya",middleName:null,surname:"Kataoka",slug:"tomoya-kataoka",fullName:"Tomoya Kataoka"},{id:"229066",title:"Prof.",name:"Kazunori",middleName:null,surname:"Kimura",slug:"kazunori-kimura",fullName:"Kazunori Kimura"}]}],onlineFirstChaptersFilter:{topicId:"18",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"81646",title:"Cortical Plasticity under Ketamine: From Synapse to Map",slug:"cortical-plasticity-under-ketamine-from-synapse-to-map",totalDownloads:14,totalDimensionsCites:0,doi:"10.5772/intechopen.104787",abstract:"Sensory systems need to process signals in a highly dynamic way to efficiently respond to variations in the animal’s environment. For instance, several studies showed that the visual system is subject to neuroplasticity since the neurons’ firing changes according to stimulus properties. This dynamic information processing might be supported by a network reorganization. Since antidepressants influence neurotransmission, they can be used to explore synaptic plasticity sustaining cortical map reorganization. To this goal, we investigated in the primary visual cortex (V1 of mouse and cat), the impact of ketamine on neuroplasticity through changes in neuronal orientation selectivity and the functional connectivity between V1 cells, using cross correlation analyses. We found that ketamine affects cortical orientation selectivity and alters the functional connectivity within an assembly. These data clearly highlight the role of the antidepressant drugs in inducing or modeling short-term plasticity in V1 which suggests that cortical processing is optimized and adapted to the properties of the stimulus.",book:{id:"11374",title:"Sensory Nervous System - Computational Neuroimaging Investigations of Topographical Organization in Human Sensory Cortex",coverURL:"https://cdn.intechopen.com/books/images_new/11374.jpg"},signatures:"Ouelhazi Afef, Rudy Lussiez and Molotchnikoff Stephane"},{id:"81582",title:"The Role of Cognitive Reserve in Executive Functioning and Its Relationship to Cognitive Decline and Dementia",slug:"the-role-of-cognitive-reserve-in-executive-functioning-and-its-relationship-to-cognitive-decline-and",totalDownloads:23,totalDimensionsCites:0,doi:"10.5772/intechopen.104646",abstract:"In this chapter, we explore how cognitive reserve is implicated in coping with the negative consequences of brain pathology and age-related cognitive decline. Individual differences in cognitive performance are based on different brain mechanisms (neural reserve and neural compensation), and reflect, among others, the effect of education, occupational attainment, leisure activities, and social involvement. These cognitive reserve proxies have been extensively associated with efficient executive functioning. We discuss and focus particularly on the compensation mechanisms related to the frontal lobe and its protective role, in maintaining cognitive performance in old age or even mitigating the clinical expression of dementia.",book:{id:"11742",title:"Neurophysiology",coverURL:"https://cdn.intechopen.com/books/images_new/11742.jpg"},signatures:"Gabriela Álvares-Pereira, Carolina Maruta and Maria Vânia Silva-Nunes"},{id:"81488",title:"Aggression and Sexual Behavior: Overlapping or Distinct Roles of 5-HT1A and 5-HT1B Receptors",slug:"aggression-and-sexual-behavior-overlapping-or-distinct-roles-of-5-ht1a-and-5-ht1b-receptors",totalDownloads:19,totalDimensionsCites:0,doi:"10.5772/intechopen.104872",abstract:"Distinct brain mechanisms for male aggressive and sexual behavior are present in mammalian species, including man. However, recent evidence suggests a strong connection and even overlap in the central nervous system (CNS) circuitry involved in aggressive and sexual behavior. The serotonergic system in the CNS is strongly involved in male aggressive and sexual behavior. In particular, 5-HT1A and 5-HT1B receptors seem to play a critical role in the modulation of these behaviors. The present chapter focuses on the effects of 5-HT1A- and 5-HT1B-receptor ligands in male rodent aggression and sexual behavior. Results indicate that 5-HT1B-heteroreceptors play a critical role in the modulation of male offensive behavior, although a definite role of 5-HT1A-auto- or heteroreceptors cannot be ruled out. 5-HT1A receptors are clearly involved in male sexual behavior, although it has to be yet unraveled whether 5-HT1A-auto- or heteroreceptors are important. Although several key nodes in the complex circuitry of aggression and sexual behavior are known, in particular in the medial hypothalamus, a clear link or connection to these critical structures and the serotonergic key receptors is yet to be determined. This information is urgently needed to detect and develop new selective anti-aggressive (serenic) and pro-sexual drugs for human applications.",book:{id:"10195",title:"Serotonin and the CNS - New Developments in Pharmacology and Therapeutics",coverURL:"https://cdn.intechopen.com/books/images_new/10195.jpg"},signatures:"Berend Olivier and Jocelien D.A. Olivier"},{id:"81093",title:"Prehospital and Emergency Room Airway Management in Traumatic Brain Injury",slug:"prehospital-and-emergency-room-airway-management-in-traumatic-brain-injury",totalDownloads:49,totalDimensionsCites:0,doi:"10.5772/intechopen.104173",abstract:"Airway management in trauma is critical and may impact patient outcomes. Particularly in traumatic brain injury (TBI), depressed level of consciousness may be associated with compromised protective airway reflexes or apnea, which can increase the risk of aspiration or result in hypoxemia and worsen the secondary brain damage. Therefore, patients with TBI and Glasgow Coma Scale (GCS) ≤ 8 have been traditionally managed by prehospital or emergency room (ER) endotracheal intubation. However, recent evidence challenged this practice and even suggested that routine intubation may be harmful. This chapter will address the indications and optimal method of securing the airway, prehospital and in the ER, in patients with traumatic brain injury.",book:{id:"11367",title:"Traumatic Brain Injury",coverURL:"https://cdn.intechopen.com/books/images_new/11367.jpg"},signatures:"Dominik A. Jakob, Jean-Cyrille Pitteloud and Demetrios Demetriades"},{id:"81011",title:"Amino Acids as Neurotransmitters. The Balance between Excitation and Inhibition as a Background for Future Clinical Applications",slug:"amino-acids-as-neurotransmitters-the-balance-between-excitation-and-inhibition-as-a-background-for-f",totalDownloads:19,totalDimensionsCites:0,doi:"10.5772/intechopen.103760",abstract:"For more than 30 years, amino acids have been well-known (and essential) participants in neurotransmission. They act as both neuromediators and metabolites in nervous tissue. Glycine and glutamic acid (glutamate) are prominent examples. These amino acids are agonists of inhibitory and excitatory membrane receptors, respectively. Moreover, they play essential roles in metabolic pathways and energy transformation in neurons and astrocytes. Despite their obvious effects on the brain, their potential role in therapeutic methods remains uncertain in clinical practice. In the current chapter, a comparison of the crosstalk between these two systems, which are responsible for excitation and inhibition in neurons, is presented. The interactions are discussed at the metabolic, receptor, and transport levels. Reaction-diffusion and a convectional flow into the interstitial fluid create a balanced distribution of glycine and glutamate. Indeed, the neurons’ final physiological state is a result of a balance between the excitatory and inhibitory influences. However, changes to the glycine and/or glutamate pools under pathological conditions can alter the state of nervous tissue. Thus, new therapies for various diseases may be developed on the basis of amino acid medication.",book:{id:"10890",title:"Recent Advances in Neurochemistry",coverURL:"https://cdn.intechopen.com/books/images_new/10890.jpg"},signatures:"Yaroslav R. Nartsissov"},{id:"80821",title:"Neuroimmunology and Neurological Manifestations of COVID-19",slug:"neuroimmunology-and-neurological-manifestations-of-covid-19",totalDownloads:41,totalDimensionsCites:0,doi:"10.5772/intechopen.103026",abstract:"Infection with SARS-CoV-2 is causing coronavirus disease in 2019 (COVID-19). Besides respiratory symptoms due to an attack on the broncho-alveolar system, COVID-19, among others, can be accompanied by neurological symptoms because of the affection of the nervous system. These can be caused by intrusion by SARS-CoV-2 of the central nervous system (CNS) and peripheral nervous system (PNS) and direct infection of local cells. In addition, neurological deterioration mediated by molecular mimicry to virus antigens or bystander activation in the context of immunological anti-virus defense can lead to tissue damage in the CNS and PNS. In addition, cytokine storm caused by SARS-CoV-2 infection in COVID-19 can lead to nervous system related symptoms. Endotheliitis of CNS vessels can lead to vessel occlusion and stroke. COVID-19 can also result in cerebral hemorrhage and sinus thrombosis possibly related to changes in clotting behavior. Vaccination is most important to prevent COVID-19 in the nervous system. There are symptomatic or/and curative therapeutic approaches to combat COVID-19 related nervous system damage that are partly still under study.",book:{id:"10890",title:"Recent Advances in Neurochemistry",coverURL:"https://cdn.intechopen.com/books/images_new/10890.jpg"},signatures:"Robert Weissert"}],onlineFirstChaptersTotal:17},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:99,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:288,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:11,numberOfOpenTopics:4,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. 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Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:9,paginationItems:[{id:"14",title:"Cell and Molecular Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",slug:"rosa-maria-martinez-espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",biography:"Dr. Rosa María Martínez-Espinosa has been a Spanish Full Professor since 2020 (Biochemistry and Molecular Biology) and is currently Vice-President of International Relations and Cooperation development and leader of the research group 'Applied Biochemistry” (University of Alicante, Spain). Other positions she has held at the university include Vice-Dean of Master Programs, Vice-Dean of the Degree in Biology and Vice-Dean for Mobility and Enterprise and Engagement at the Faculty of Science (University of Alicante). She received her Bachelor in Biology in 1998 (University of Alicante) and her PhD in 2003 (Biochemistry, University of Alicante). She undertook post-doctoral research at the University of East Anglia (Norwich, U.K. 2004-2005; 2007-2008).\nHer multidisciplinary research focuses on investigating archaea and their potential applications in biotechnology. She has an H-index of 21. She has authored one patent and has published more than 70 indexed papers and around 60 book chapters.\nShe has contributed to more than 150 national and international meetings during the last 15 years. Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",slug:"ana-isabel-flores",fullName:"Ana Isabel Flores",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRpIOQA0/Profile_Picture_1632418099564",institutionString:null,institution:{name:"Hospital Universitario 12 De Octubre",institutionURL:null,country:{name:"Spain"}}},{id:"328234",title:"Ph.D.",name:"Christian",middleName:null,surname:"Palavecino",slug:"christian-palavecino",fullName:"Christian Palavecino",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000030DhEhQAK/Profile_Picture_1628835318625",institutionString:null,institution:{name:"Central University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",slug:"francisco-javier-martin-romero",fullName:"Francisco Javier Martin-Romero",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",institutionString:null,institution:{name:"University of Extremadura",institutionURL:null,country:{name:"Spain"}}}]},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. He performed post-doctoral studies at Max-Planck Institute, Germany, and University of Florence, Italy in addition to making several scientific visits abroad. He currently works as a Full Professor of Biochemistry in the Faculty of Pharmacy, Anadolu University, Turkey. Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. Dr. Beydemir is also Rector of Bilecik Şeyh Edebali University, Turkey.",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",slug:"deniz-ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",biography:"Dr. Deniz Ekinci obtained a BSc in Chemistry in 2004, MSc in Biochemistry in 2006, and PhD in Biochemistry in 2009 from Atatürk University, Turkey. He studied at Stetson University, USA, in 2007-2008 and at the Max Planck Institute of Molecular Cell Biology and Genetics, Germany, in 2009-2010. Dr. Ekinci currently works as a Full Professor of Biochemistry in the Faculty of Agriculture and is the Head of the Enzyme and Microbial Biotechnology Division, Ondokuz Mayıs University, Turkey. He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. 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He was associate professor at the University of Limoges (1987) before becoming full professor of biochemistry at the Université d’Artois (1996). He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. His teaching areas are energy metabolism and regulation, integration and organ specialization and metabolic adaptation.",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",slug:"anca-pantea-stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",slug:"attilio-rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",slug:"yanfei-(jacob)-qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",slug:"paolo-iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",biography:"Paolo Iadarola graduated with a degree in Chemistry from the University of Pavia (Italy) in July 1972. He then worked as an Assistant Professor at the Faculty of Science of the same University until 1984. In 1985, Prof. Iadarola became Associate Professor at the Department of Biology and Biotechnologies of the University of Pavia and retired in October 2017. Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. In this context, he has developed and validated new methodologies (e.g., Capillary Electrophoresis coupled to Laser-Induced Fluorescence, CE-LIF) whose application enabled him to determine both the amounts of biochemical markers (Desmosines) in urine/serum of patients affected by Chronic Obstructive Pulmonary Disease (COPD) and the activity of proteolytic enzymes (Human Neutrophil Elastase, Cathepsin G, Pseudomonas aeruginosa elastase) in sputa of these patients. More recently, Prof. Iadarola was involved in developing techniques such as two-dimensional electrophoresis coupled to liquid chromatography/mass spectrometry (2DE-LC/MS) for the proteomic analysis of biological fluids aimed at the identification of potential biomarkers of different lung diseases. He is the author of about 150 publications (According to Scopus: H-Index: 23; Total citations: 1568- According to WOS: H-Index: 20; Total Citations: 1296) of peer-reviewed international journals. He is a Consultant Reviewer for several journals, including the Journal of Chromatography A, Journal of Chromatography B, Plos ONE, Proteomes, International Journal of Molecular Science, Biotech, Electrophoresis, and others. He is also Associate Editor of Biotech.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",slug:"simona-viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",biography:"Simona Viglio is an Associate Professor of Biochemistry at the Department of Molecular Medicine at the University of Pavia. She has been working since 1995 on the determination of proteolytic enzymes involved in the degradation process of connective tissue matrix and on the identification of biological markers of lung diseases. She gained considerable experience in developing and validating new methodologies whose applications allowed her to determine both the amount of biomarkers (Desmosine and Isodesmosine) in the urine of patients affected by COPD, and the activity of proteolytic enzymes (HNE, Cathepsin G, Pseudomonas aeruginosa elastase) in the sputa of these patients. Simona Viglio was also involved in research dealing with the supplementation of amino acids in patients with brain injury and chronic heart failure. She is presently engaged in the development of 2-DE and LC-MS techniques for the study of proteomics in biological fluids. The aim of this research is the identification of potential biomarkers of lung diseases. 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He is also a faculty member in the Molecular Oncology Program. He obtained his MSc and Ph.D. at Oregon State University and Texas Tech University, respectively. He pursued his postdoctoral studies at Rutgers University Medical School and the National Institutes of Health (NIH/NIDDK), USA. His research focuses on biochemistry, biophysics, genetics, molecular biology, and molecular medicine with specialization in the fields of drug design, protein structure-function, protein folding, prions, microRNA, pseudogenes, molecular cancer, epigenetics, metabolites, proteomics, genomics, protein expression, and characterization by spectroscopic and calorimetric methods.",institutionString:"University of Health Sciences",institution:null},{id:"180528",title:"Dr.",name:"Hiroyuki",middleName:null,surname:"Kagechika",slug:"hiroyuki-kagechika",fullName:"Hiroyuki Kagechika",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/180528/images/system/180528.jpg",biography:"Hiroyuki Kagechika received his bachelor’s degree and Ph.D. in Pharmaceutical Sciences from the University of Tokyo, Japan, where he served as an associate professor until 2004. He is currently a professor at the Institute of Biomaterials and Bioengineering (IBB), Tokyo Medical and Dental University (TMDU). From 2010 to 2012, he was the dean of the Graduate School of Biomedical Science. Since 2012, he has served as the vice dean of the Graduate School of Medical and Dental Sciences. He has been the director of the IBB since 2020. Dr. Kagechika’s major research interests are the medicinal chemistry of retinoids, vitamins D/K, and nuclear receptors. He has developed various compounds including a drug for acute promyelocytic leukemia.",institutionString:"Tokyo Medical and Dental University",institution:{name:"Tokyo Medical and Dental University",country:{name:"Japan"}}},{id:"40482",title:null,name:"Rizwan",middleName:null,surname:"Ahmad",slug:"rizwan-ahmad",fullName:"Rizwan Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/40482/images/system/40482.jpeg",biography:"Dr. Rizwan Ahmad is a University Professor and Coordinator, Quality and Development, College of Medicine, Imam Abdulrahman bin Faisal University, Saudi Arabia. Previously, he was Associate Professor of Human Function, Oman Medical College, Oman, and SBS University, Dehradun. Dr. Ahmad completed his education at Aligarh Muslim University, Aligarh. He has published several articles in peer-reviewed journals, chapters, and edited books. His area of specialization is free radical biochemistry and autoimmune diseases.",institutionString:"Imam Abdulrahman Bin Faisal University",institution:{name:"Imam Abdulrahman Bin Faisal University",country:{name:"Saudi Arabia"}}},{id:"41865",title:"Prof.",name:"Farid A.",middleName:null,surname:"Badria",slug:"farid-a.-badria",fullName:"Farid A. Badria",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/41865/images/system/41865.jpg",biography:"Farid A. Badria, Ph.D., is the recipient of several awards, including The World Academy of Sciences (TWAS) Prize for Public Understanding of Science; the World Intellectual Property Organization (WIPO) Gold Medal for best invention; Outstanding Arab Scholar, Kuwait; and the Khwarizmi International Award, Iran. He has 250 publications, 12 books, 20 patents, and several marketed pharmaceutical products to his credit. He continues to lead research projects on developing new therapies for liver, skin disorders, and cancer. Dr. Badria was listed among the world’s top 2% of scientists in medicinal and biomolecular chemistry in 2019 and 2020. He is a member of the Arab Development Fund, Kuwait; International Cell Research Organization–United Nations Educational, Scientific and Cultural Organization (ICRO–UNESCO), Chile; and UNESCO Biotechnology France",institutionString:"Mansoura University",institution:{name:"Mansoura University",country:{name:"Egypt"}}},{id:"329385",title:"Dr.",name:"Rajesh K.",middleName:"Kumar",surname:"Singh",slug:"rajesh-k.-singh",fullName:"Rajesh K. Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329385/images/system/329385.png",biography:"Dr. Singh received a BPharm (2003) and MPharm (2005) from Panjab University, Chandigarh, India, and a Ph.D. (2013) from Punjab Technical University (PTU), Jalandhar, India. He has more than sixteen years of teaching experience and has supervised numerous postgraduate and Ph.D. students. He has to his credit more than seventy papers in SCI- and SCOPUS-indexed journals, fifty-five conference proceedings, four books, six Best Paper Awards, and five projects from different government agencies. He is currently an editorial board member of eight international journals and a reviewer for more than fifty scientific journals. He received Top Reviewer and Excellent Peer Reviewer Awards from Publons in 2016 and 2017, respectively. He is also on the panel of The International Reviewer for reviewing research proposals for grants from the Royal Society. He also serves as a Publons Academy mentor and Bentham brand ambassador.",institutionString:"Punjab Technical University",institution:{name:"Punjab Technical University",country:{name:"India"}}},{id:"142388",title:"Dr.",name:"Thiago",middleName:"Gomes",surname:"Gomes Heck",slug:"thiago-gomes-heck",fullName:"Thiago Gomes Heck",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/142388/images/7259_n.jpg",biography:null,institutionString:null,institution:{name:"Universidade Regional do Noroeste do Estado do Rio Grande do Sul",country:{name:"Brazil"}}},{id:"336273",title:"Assistant Prof.",name:"Janja",middleName:null,surname:"Zupan",slug:"janja-zupan",fullName:"Janja Zupan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/336273/images/14853_n.jpeg",biography:"Janja Zupan graduated in 2005 at the Department of Clinical Biochemistry (superviser prof. dr. Janja Marc) in the field of genetics of osteoporosis. Since November 2009 she is working as a Teaching Assistant at the Faculty of Pharmacy, Department of Clinical Biochemistry. In 2011 she completed part of her research and PhD work at Institute of Genetics and Molecular Medicine, University of Edinburgh. She finished her PhD entitled The influence of the proinflammatory cytokines on the RANK/RANKL/OPG in bone tissue of osteoporotic and osteoarthritic patients in 2012. From 2014-2016 she worked at the Institute of Biomedical Sciences, University of Aberdeen as a postdoctoral research fellow on UK Arthritis research project where she gained knowledge in mesenchymal stem cells and regenerative medicine. She returned back to University of Ljubljana, Faculty of Pharmacy in 2016. She is currently leading project entitled Mesenchymal stem cells-the keepers of tissue endogenous regenerative capacity facing up to aging of the musculoskeletal system funded by Slovenian Research Agency.",institutionString:null,institution:{name:"University of Ljubljana",country:{name:"Slovenia"}}},{id:"357453",title:"Dr.",name:"Radheshyam",middleName:null,surname:"Maurya",slug:"radheshyam-maurya",fullName:"Radheshyam Maurya",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/357453/images/16535_n.jpg",biography:null,institutionString:null,institution:{name:"University of Hyderabad",country:{name:"India"}}},{id:"311457",title:"Dr.",name:"Júlia",middleName:null,surname:"Scherer Santos",slug:"julia-scherer-santos",fullName:"Júlia Scherer Santos",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/311457/images/system/311457.jpg",biography:"Dr. Júlia Scherer Santos works in the areas of cosmetology, nanotechnology, pharmaceutical technology, beauty, and aesthetics. Dr. Santos also has experience as a professor of graduate courses. Graduated in Pharmacy, specialization in Cosmetology and Cosmeceuticals applied to aesthetics, specialization in Aesthetic and Cosmetic Health, and a doctorate in Pharmaceutical Nanotechnology. Teaching experience in Pharmacy and Aesthetics and Cosmetics courses. She works mainly on the following subjects: nanotechnology, cosmetology, pharmaceutical technology, aesthetics.",institutionString:"Universidade Federal de Juiz de Fora",institution:{name:"Universidade Federal de Juiz de Fora",country:{name:"Brazil"}}},{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",slug:"abdulsamed-kukurt",fullName:"Abdulsamed Kükürt",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNVJQA4/Profile_Picture_2022-03-07T13:23:04.png",biography:"Dr. Kükürt graduated from Uludağ University in Turkey. He started his academic career as a Research Assistant in the Department of Biochemistry at Kafkas University. In 2019, he completed his Ph.D. program in the Department of Biochemistry at the Institute of Health Sciences. He is currently working at the Department of Biochemistry, Kafkas University. He has 27 published research articles in academic journals, 11 book chapters, and 37 papers. He took part in 10 academic projects. He served as a reviewer for many articles. He still serves as a member of the review board in many academic journals.",institutionString:null,institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"178366",title:"Associate Prof.",name:"Volkan",middleName:null,surname:"Gelen",slug:"volkan-gelen",fullName:"Volkan Gelen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178366/images/system/178366.jpg",biography:"Volkan Gelen is a Physiology specialist who received his veterinary degree from Kafkas University in 2011. Between 2011-2015, he worked as an assistant at Atatürk University, Faculty of Veterinary Medicine, Department of Physiology. In 2016, he joined Kafkas University, Faculty of Veterinary Medicine, Department of Physiology as an assistant professor. Dr. Gelen has been engaged in various academic activities at Kafkas University since 2016. There he completed 5 projects and has 3 ongoing projects. He has 60 articles published in scientific journals and 20 poster presentations in scientific congresses. His research interests include physiology, endocrine system, cancer, diabetes, cardiovascular system diseases, and isolated organ bath system studies.",institutionString:"Kafkas University",institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"418963",title:"Dr.",name:"Augustine Ododo",middleName:"Augustine",surname:"Osagie",slug:"augustine-ododo-osagie",fullName:"Augustine Ododo Osagie",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/418963/images/16900_n.jpg",biography:"Born into the family of Osagie, a prince of the Benin Kingdom. I am currently an academic in the Department of Medical Biochemistry, University of Benin. Part of the duties are to teach undergraduate students and conduct academic research.",institutionString:null,institution:{name:"University of Benin",country:{name:"Nigeria"}}},{id:"192992",title:"Prof.",name:"Shagufta",middleName:null,surname:"Perveen",slug:"shagufta-perveen",fullName:"Shagufta Perveen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192992/images/system/192992.png",biography:"Prof. Shagufta Perveen is a Distinguish Professor in the Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia. Dr. Perveen has acted as the principal investigator of major research projects funded by the research unit of King Saud University. She has more than ninety original research papers in peer-reviewed journals of international repute to her credit. She is a fellow member of the Royal Society of Chemistry UK and the American Chemical Society of the United States.",institutionString:"King Saud University",institution:{name:"King Saud University",country:{name:"Saudi Arabia"}}},{id:"49848",title:"Dr.",name:"Wen-Long",middleName:null,surname:"Hu",slug:"wen-long-hu",fullName:"Wen-Long Hu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49848/images/system/49848.jpg",biography:"Wen-Long Hu is Chief of the Division of Acupuncture, Department of Chinese Medicine at Kaohsiung Chang Gung Memorial Hospital, as well as an adjunct associate professor at Fooyin University and Kaohsiung Medical University. Wen-Long is President of Taiwan Traditional Chinese Medicine Medical Association. He has 28 years of experience in clinical practice in laser acupuncture therapy and 34 years in acupuncture. He is an invited speaker for lectures and workshops in laser acupuncture at many symposiums held by medical associations. He owns the patent for herbal preparation and producing, and for the supercritical fluid-treated needle. Dr. Hu has published three books, 12 book chapters, and more than 30 papers in reputed journals, besides serving as an editorial board member of repute.",institutionString:"Kaohsiung Chang Gung Memorial Hospital",institution:{name:"Kaohsiung Chang Gung Memorial Hospital",country:{name:"Taiwan"}}},{id:"298472",title:"Prof.",name:"Andrey V.",middleName:null,surname:"Grechko",slug:"andrey-v.-grechko",fullName:"Andrey V. Grechko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/298472/images/system/298472.png",biography:"Andrey Vyacheslavovich Grechko, Ph.D., Professor, is a Corresponding Member of the Russian Academy of Sciences. He graduated from the Semashko Moscow Medical Institute (Semashko National Research Institute of Public Health) with a degree in Medicine (1998), the Clinical Department of Dermatovenerology (2000), and received a second higher education in Psychology (2009). Professor A.V. Grechko held the position of Сhief Physician of the Central Clinical Hospital in Moscow. He worked as a professor at the faculty and was engaged in scientific research at the Medical University. Starting in 2013, he has been the initiator of the creation of the Federal Scientific and Clinical Center for Intensive Care and Rehabilitology, Moscow, Russian Federation, where he also serves as Director since 2015. He has many years of experience in research and teaching in various fields of medicine, is an author/co-author of more than 200 scientific publications, 13 patents, 15 medical books/chapters, including Chapter in Book «Metabolomics», IntechOpen, 2020 «Metabolomic Discovery of Microbiota Dysfunction as the Cause of Pathology».",institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"199461",title:"Prof.",name:"Natalia V.",middleName:null,surname:"Beloborodova",slug:"natalia-v.-beloborodova",fullName:"Natalia V. Beloborodova",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/199461/images/system/199461.jpg",biography:'Natalia Vladimirovna Beloborodova was educated at the Pirogov Russian National Research Medical University, with a degree in pediatrics in 1980, a Ph.D. in 1987, and a specialization in Clinical Microbiology from First Moscow State Medical University in 2004. She has been a Professor since 1996. Currently, she is the Head of the Laboratory of Metabolism, a division of the Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russian Federation. N.V. Beloborodova has many years of clinical experience in the field of intensive care and surgery. She studies infectious complications and sepsis. She initiated a series of interdisciplinary clinical and experimental studies based on the concept of integrating human metabolism and its microbiota. Her scientific achievements are widely known: she is the recipient of the Marie E. Coates Award \\"Best lecturer-scientist\\" Gustafsson Fund, Karolinska Institutes, Stockholm, Sweden, and the International Sepsis Forum Award, Pasteur Institute, Paris, France (2014), etc. Professor N.V. Beloborodova wrote 210 papers, five books, 10 chapters and has edited four books.',institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"354260",title:"Ph.D.",name:"Tércio Elyan",middleName:"Azevedo",surname:"Azevedo Martins",slug:"tercio-elyan-azevedo-martins",fullName:"Tércio Elyan Azevedo Martins",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/354260/images/16241_n.jpg",biography:"Graduated in Pharmacy from the Federal University of Ceará with the modality in Industrial Pharmacy, Specialist in Production and Control of Medicines from the University of São Paulo (USP), Master in Pharmaceuticals and Medicines from the University of São Paulo (USP) and Doctor of Science in the program of Pharmaceuticals and Medicines by the University of São Paulo. Professor at Universidade Paulista (UNIP) in the areas of chemistry, cosmetology and trichology. Assistant Coordinator of the Higher Course in Aesthetic and Cosmetic Technology at Universidade Paulista Campus Chácara Santo Antônio. Experience in the Pharmacy area, with emphasis on Pharmacotechnics, Pharmaceutical Technology, Research and Development of Cosmetics, acting mainly on topics such as cosmetology, antioxidant activity, aesthetics, photoprotection, cyclodextrin and thermal analysis.",institutionString:null,institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"334285",title:"Ph.D. Student",name:"Sameer",middleName:"Kumar",surname:"Jagirdar",slug:"sameer-jagirdar",fullName:"Sameer Jagirdar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334285/images/14691_n.jpg",biography:"I\\'m a graduate student at the center for biosystems science and engineering at the Indian Institute of Science, Bangalore, India. I am interested in studying host-pathogen interactions at the biomaterial interface.",institutionString:null,institution:{name:"Indian Institute of Science Bangalore",country:{name:"India"}}},{id:"329795",title:"Dr.",name:"Mohd Aftab",middleName:"Aftab",surname:"Siddiqui",slug:"mohd-aftab-siddiqui",fullName:"Mohd Aftab Siddiqui",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329795/images/15648_n.jpg",biography:"Dr. Mohd Aftab Siddiqui is currently working as Assistant Professor in the Faculty of Pharmacy, Integral University, Lucknow for the last 6 years. He has completed his Doctor in Philosophy (Pharmacology) in 2020 from Integral University, Lucknow. He completed his Bachelor in Pharmacy in 2013 and Master in Pharmacy (Pharmacology) in 2015 from Integral University, Lucknow. He is the gold medalist in Bachelor and Master degree. He qualified GPAT -2013, GPAT -2014, and GPAT 2015. His area of research is Pharmacological screening of herbal drugs/ natural products in liver and cardiac diseases. He has guided many M. Pharm. research projects. He has many national and international publications.",institutionString:"Integral University",institution:null},{id:"255360",title:"Dr.",name:"Usama",middleName:null,surname:"Ahmad",slug:"usama-ahmad",fullName:"Usama Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255360/images/system/255360.png",biography:"Dr. Usama Ahmad holds a specialization in Pharmaceutics from Amity University, Lucknow, India. He received his Ph.D. degree from Integral University. Currently, he’s working as an Assistant Professor of Pharmaceutics in the Faculty of Pharmacy, Integral University. From 2013 to 2014 he worked on a research project funded by SERB-DST, Government of India. He has a rich publication record with more than 32 original articles published in reputed journals, 3 edited books, 5 book chapters, and a number of scientific articles published in ‘Ingredients South Asia Magazine’ and ‘QualPharma Magazine’. He is a member of the American Association for Cancer Research, International Association for the Study of Lung Cancer, and the British Society for Nanomedicine. Dr. Ahmad’s research focus is on the development of nanoformulations to facilitate the delivery of drugs that aim to provide practical solutions to current healthcare problems.",institutionString:"Integral University",institution:{name:"Integral University",country:{name:"India"}}},{id:"30568",title:"Prof.",name:"Madhu",middleName:null,surname:"Khullar",slug:"madhu-khullar",fullName:"Madhu Khullar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/30568/images/system/30568.jpg",biography:"Dr. Madhu Khullar is a Professor of Experimental Medicine and Biotechnology at the Post Graduate Institute of Medical Education and Research, Chandigarh, India. She completed her Post Doctorate in hypertension research at the Henry Ford Hospital, Detroit, USA in 1985. She is an editor and reviewer of several international journals, and a fellow and member of several cardiovascular research societies. Dr. Khullar has a keen research interest in genetics of hypertension, and is currently studying pharmacogenetics of hypertension.",institutionString:"Post Graduate Institute of Medical Education and Research",institution:{name:"Post Graduate Institute of Medical Education and Research",country:{name:"India"}}},{id:"223233",title:"Prof.",name:"Xianquan",middleName:null,surname:"Zhan",slug:"xianquan-zhan",fullName:"Xianquan Zhan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/223233/images/system/223233.png",biography:"Xianquan Zhan received his MD and Ph.D. in Preventive Medicine at West China University of Medical Sciences. He received his post-doctoral training in oncology and cancer proteomics at the Central South University, China, and the University of Tennessee Health Science Center (UTHSC), USA. He worked at UTHSC and the Cleveland Clinic in 2001–2012 and achieved the rank of associate professor at UTHSC. Currently, he is a full professor at Central South University and Shandong First Medical University, and an advisor to MS/PhD students and postdoctoral fellows. He is also a fellow of the Royal Society of Medicine and European Association for Predictive Preventive Personalized Medicine (EPMA), a national representative of EPMA, and a member of the American Society of Clinical Oncology (ASCO) and the American Association for the Advancement of Sciences (AAAS). He is also the editor in chief of International Journal of Chronic Diseases & Therapy, an associate editor of EPMA Journal, Frontiers in Endocrinology, and BMC Medical Genomics, and a guest editor of Mass Spectrometry Reviews, Frontiers in Endocrinology, EPMA Journal, and Oxidative Medicine and Cellular Longevity. He has published more than 148 articles, 28 book chapters, 6 books, and 2 US patents in the field of clinical proteomics and biomarkers.",institutionString:"Shandong First Medical University",institution:{name:"Affiliated Hospital of Shandong Academy of Medical Sciences",country:{name:"China"}}},{id:"297507",title:"Dr.",name:"Charles",middleName:"Elias",surname:"Assmann",slug:"charles-assmann",fullName:"Charles Assmann",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/297507/images/system/297507.jpg",biography:"Charles Elias Assmann is a biologist from Federal University of Santa Maria (UFSM, Brazil), who spent some time abroad at the Ludwig-Maximilians-Universität München (LMU, Germany). He has Masters Degree in Biochemistry (UFSM), and is currently a PhD student at Biochemistry at the Department of Biochemistry and Molecular Biology of the UFSM. His areas of expertise include: Biochemistry, Molecular Biology, Enzymology, Genetics and Toxicology. He is currently working on the following subjects: Aluminium toxicity, Neuroinflammation, Oxidative stress and Purinergic system. Since 2011 he has presented more than 80 abstracts in scientific proceedings of national and international meetings. Since 2014, he has published more than 20 peer reviewed papers (including 4 reviews, 3 in Portuguese) and 2 book chapters. He has also been a reviewer of international journals and ad hoc reviewer of scientific committees from Brazilian Universities.",institutionString:"Universidade Federal de Santa Maria",institution:{name:"Universidade Federal de Santa Maria",country:{name:"Brazil"}}},{id:"217850",title:"Dr.",name:"Margarete Dulce",middleName:null,surname:"Bagatini",slug:"margarete-dulce-bagatini",fullName:"Margarete Dulce Bagatini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/217850/images/system/217850.jpeg",biography:"Dr. Margarete Dulce Bagatini is an associate professor at the Federal University of Fronteira Sul/Brazil. She has a degree in Pharmacy and a PhD in Biological Sciences: Toxicological Biochemistry. She is a member of the UFFS Research Advisory Committee\nand a member of the Biovitta Research Institute. She is currently:\nthe leader of the research group: Biological and Clinical Studies\nin Human Pathologies, professor of postgraduate program in\nBiochemistry at UFSC and postgraduate program in Science and Food Technology at\nUFFS. She has experience in the area of pharmacy and clinical analysis, acting mainly\non the following topics: oxidative stress, the purinergic system and human pathologies, being a reviewer of several international journals and books.",institutionString:"Universidade Federal da Fronteira Sul",institution:{name:"Universidade Federal da Fronteira Sul",country:{name:"Brazil"}}},{id:"226275",title:"Ph.D.",name:"Metin",middleName:null,surname:"Budak",slug:"metin-budak",fullName:"Metin Budak",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226275/images/system/226275.jfif",biography:"Metin Budak, MSc, PhD is an Assistant Professor at Trakya University, Faculty of Medicine. He has been Head of the Molecular Research Lab at Prof. Mirko Tos Ear and Hearing Research Center since 2018. His specializations are biophysics, epigenetics, genetics, and methylation mechanisms. He has published around 25 peer-reviewed papers, 2 book chapters, and 28 abstracts. He is a member of the Clinical Research Ethics Committee and Quantification and Consideration Committee of Medicine Faculty. His research area is the role of methylation during gene transcription, chromatin packages DNA within the cell and DNA repair, replication, recombination, and gene transcription. His research focuses on how the cell overcomes chromatin structure and methylation to allow access to the underlying DNA and enable normal cellular function.",institutionString:"Trakya University",institution:{name:"Trakya University",country:{name:"Turkey"}}},{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",slug:"anca-pantea-stoian",fullName:"Anca Pantea Stoian",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",biography:"Anca Pantea Stoian is a specialist in diabetes, nutrition, and metabolic diseases as well as health food hygiene. She also has competency in general ultrasonography.\n\nShe is an associate professor in the Diabetes, Nutrition and Metabolic Diseases Department, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania. She has been chief of the Hygiene Department, Faculty of Dentistry, at the same university since 2019. Her interests include micro and macrovascular complications in diabetes and new therapies. Her research activities focus on nutritional intervention in chronic pathology, as well as cardio-renal-metabolic risk assessment, and diabetes in cancer. She is currently engaged in developing new therapies and technological tools for screening, prevention, and patient education in diabetes. \n\nShe is a member of the European Association for the Study of Diabetes, Cardiometabolic Academy, CEDA, Romanian Society of Diabetes, Nutrition and Metabolic Diseases, Romanian Diabetes Federation, and Association for Renal Metabolic and Nutrition studies. She has authored or co-authored 160 papers in national and international peer-reviewed journals.",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",country:{name:"Romania"}}},{id:"279792",title:"Dr.",name:"João",middleName:null,surname:"Cotas",slug:"joao-cotas",fullName:"João Cotas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/279792/images/system/279792.jpg",biography:"Graduate and master in Biology from the University of Coimbra.\n\nI am a research fellow at the Macroalgae Laboratory Unit, in the MARE-UC – Marine and Environmental Sciences Centre of the University of Coimbra. My principal function is the collection, extraction and purification of macroalgae compounds, chemical and bioactive characterization of the compounds and algae extracts and development of new methodologies in marine biotechnology area. \nI am associated in two projects: one consists on discovery of natural compounds for oncobiology. The other project is the about the natural compounds/products for agricultural area.\n\nPublications:\nCotas, J.; Figueirinha, A.; Pereira, L.; Batista, T. 2018. An analysis of the effects of salinity on Fucus ceranoides (Ochrophyta, Phaeophyceae), in the Mondego River (Portugal). Journal of Oceanology and Limnology. in press. DOI: 10.1007/s00343-019-8111-3",institutionString:"Faculty of Sciences and Technology of University of Coimbra",institution:null},{id:"279788",title:"Dr.",name:"Leonel",middleName:null,surname:"Pereira",slug:"leonel-pereira",fullName:"Leonel Pereira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/279788/images/system/279788.jpg",biography:"Leonel Pereira has an undergraduate degree in Biology, a Ph.D. in Biology (specialty in Cell Biology), and a Habilitation degree in Biosciences (specialization in Biotechnology) from the Faculty of Science and Technology, University of Coimbra, Portugal, where he is currently a professor. In addition to teaching at this university, he is an integrated researcher at the Marine and Environmental Sciences Center (MARE), Portugal. His interests include marine biodiversity (algae), marine biotechnology (algae bioactive compounds), and marine ecology (environmental assessment). Since 2008, he has been the author and editor of the electronic publication MACOI – Portuguese Seaweeds Website (www.seaweeds.uc.pt). He is also a member of the editorial boards of several scientific journals. Dr. Pereira has edited or authored more than 20 books, 100 journal articles, and 45 book chapters. He has given more than 100 lectures and oral communications at various national and international scientific events. He is the coordinator of several national and international research projects. In 1998, he received the Francisco de Holanda Award (Honorable Mention) and, more recently, the Mar Rei D. Carlos award (18th edition). He is also a winner of the 2016 CHOICE Award for an outstanding academic title for his book Edible Seaweeds of the World. In 2020, Dr. Pereira received an Honorable Mention for the Impact of International Publications from the Web of Science",institutionString:"University of Coimbra",institution:{name:"University of Coimbra",country:{name:"Portugal"}}},{id:"61946",title:"Dr.",name:"Carol",middleName:null,surname:"Bernstein",slug:"carol-bernstein",fullName:"Carol Bernstein",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/61946/images/system/61946.jpg",biography:"Carol Bernstein received her PhD in Genetics from the University of California (Davis). She was a faculty member at the University of Arizona College of Medicine for 43 years, retiring in 2011. Her research interests focus on DNA damage and its underlying role in sex, aging and in the early steps of initiation and progression to cancer. In her research, she had used organisms including bacteriophage T4, Neurospora crassa, Schizosaccharomyces pombe and mice, as well as human cells and tissues. She authored or co-authored more than 140 scientific publications, including articles in major peer reviewed journals, book chapters, invited reviews and one book.",institutionString:"University of Arizona",institution:{name:"University of Arizona",country:{name:"United States of America"}}},{id:"182258",title:"Dr.",name:"Ademar",middleName:"Pereira",surname:"Serra",slug:"ademar-serra",fullName:"Ademar Serra",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/182258/images/system/182258.jpeg",biography:"Dr. Serra studied Agronomy on Universidade Federal de Mato Grosso do Sul (UFMS) (2005). He received master degree in Agronomy, Crop Science (Soil fertility and plant nutrition) (2007) by Universidade Federal da Grande Dourados (UFGD), and PhD in agronomy (Soil fertility and plant nutrition) (2011) from Universidade Federal da Grande Dourados / Escola Superior de Agricultura Luiz de Queiroz (UFGD/ESALQ-USP). Dr. Serra is currently working at Brazilian Agricultural Research Corporation (EMBRAPA). His research focus is on mineral nutrition of plants, crop science and soil science. Dr. Serra\\'s current projects are soil organic matter, soil phosphorus fractions, compositional nutrient diagnosis (CND) and isometric log ratio (ilr) transformation in compositional data analysis.",institutionString:"Brazilian Agricultural Research Corporation",institution:{name:"Brazilian Agricultural Research Corporation",country:{name:"Brazil"}}}]}},subseries:{item:{id:"23",type:"subseries",title:"Computational Neuroscience",keywords:"Single-Neuron Modeling, Sensory Processing, Motor Control, Memory and Synaptic Pasticity, Attention, Identification, Categorization, Discrimination, Learning, Development, Axonal Patterning and Guidance, Neural Architecture, Behaviours and Dynamics of Networks, Cognition and the Neuroscientific Basis of Consciousness",scope:"Computational neuroscience focuses on biologically realistic abstractions and models validated and solved through computational simulations to understand principles for the development, structure, physiology, and ability of the nervous system. This topic is dedicated to biologically plausible descriptions and computational models - at various abstraction levels - of neurons and neural systems. This includes, but is not limited to: single-neuron modeling, sensory processing, motor control, memory, and synaptic plasticity, attention, identification, categorization, discrimination, learning, development, axonal patterning, guidance, neural architecture, behaviors, and dynamics of networks, cognition and the neuroscientific basis of consciousness. Particularly interesting are models of various types of more compound functions and abilities, various and more general fundamental principles (e.g., regarding architecture, organization, learning, development, etc.) found at various spatial and temporal levels.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",hasOnlineFirst:!1,hasPublishedBooks:!0,annualVolume:11419,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null,series:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403"},editorialBoard:[{id:"13818",title:"Dr.",name:"Asim",middleName:null,surname:"Bhatti",slug:"asim-bhatti",fullName:"Asim Bhatti",profilePictureURL:"https://mts.intechopen.com/storage/users/13818/images/system/13818.jpg",institutionString:null,institution:{name:"Deakin University",institutionURL:null,country:{name:"Australia"}}},{id:"151889",title:"Dr.",name:"Joao Luis Garcia",middleName:null,surname:"Rosa",slug:"joao-luis-garcia-rosa",fullName:"Joao Luis Garcia Rosa",profilePictureURL:"https://mts.intechopen.com/storage/users/151889/images/4861_n.jpg",institutionString:null,institution:{name:"University of Sao Paulo",institutionURL:null,country:{name:"Brazil"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",institutionURL:null,country:{name:"Turkey"}}}]},onlineFirstChapters:{paginationCount:1,paginationItems:[{id:"81644",title:"Perspective Chapter: Ethics of Using Placebo Controlled Trials for Covid-19 Vaccine Development in Vulnerable Populations",doi:"10.5772/intechopen.104776",signatures:"Lesley Burgess, Jurie Jordaan and Matthew Wilson",slug:"perspective-chapter-ethics-of-using-placebo-controlled-trials-for-covid-19-vaccine-development-in-vu",totalDownloads:9,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"SARS-CoV-2 Variants - 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