\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"98",leadTitle:null,fullTitle:"Evolutionary Algorithms",title:"Evolutionary Algorithms",subtitle:null,reviewType:"peer-reviewed",abstract:"Evolutionary algorithms are successively applied to wide optimization problems in the engineering, marketing, operations research, and social science, such as include scheduling, genetics, material selection, structural design and so on. Apart from mathematical optimization problems, evolutionary algorithms have also been used as an experimental framework within biological evolution and natural selection in the field of artificial life.",isbn:null,printIsbn:"978-953-307-171-8",pdfIsbn:"978-953-51-4493-9",doi:"10.5772/627",price:159,priceEur:175,priceUsd:205,slug:"evolutionary-algorithms",numberOfPages:598,isOpenForSubmission:!1,isInWos:1,isInBkci:!0,hash:"6816724ee9d4c10832441d90fd28a485",bookSignature:"Eisuke Kita",publishedDate:"April 26th 2011",coverURL:"https://cdn.intechopen.com/books/images_new/98.jpg",numberOfDownloads:73473,numberOfWosCitations:98,numberOfCrossrefCitations:80,numberOfCrossrefCitationsByBook:7,numberOfDimensionsCitations:138,numberOfDimensionsCitationsByBook:7,hasAltmetrics:0,numberOfTotalCitations:316,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 25th 2010",dateEndSecondStepPublish:"June 22nd 2010",dateEndThirdStepPublish:"September 27th 2010",dateEndFourthStepPublish:"November 26th 2010",dateEndFifthStepPublish:"February 9th 2011",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7,8",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"22506",title:"Prof.",name:"Eisuke",middleName:null,surname:"Kita",slug:"eisuke-kita",fullName:"Eisuke Kita",profilePictureURL:"https://mts.intechopen.com/storage/users/22506/images/1591_n.jpg",biography:"Eisuke Kita was born in Japan in 1964. He moved straight from high school to School of Engineering of Mie University. After getting the bachelor and the master degree, he moved to Graduate School of Mechanical Engineering of the Nagoya University and graduated with the Doctor of Engineering in 1991. He spent 9 years in the School of Mechanical Engineering as a lecturer and an assistant professor, and 11 years in the School of Informatics and Science as an associate professor. He became, in 2009, the full professor of the Graduate School of Information Science of the Nagoya University. His publications include numerical analysis schemes, multi-agent traffic simulation, artificial market simulation, application of Bayesian network and so on. He earned the honor as Encouraging prize of Japan Society of Mechanical Engineering in 2000, Encouraging prize of Computer Science Committee of Information Processing Society of Japan in 2007 and 2009.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:null}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"590",title:"Algorithm Analysis",slug:"numerical-analysis-and-scientific-computing-algorithm-analysis"}],chapters:[{id:"15613",title:"Hybridization of Evolutionary Algorithms",doi:"10.5772/15592",slug:"hybridization-of-evolutionary-algorithms",totalDownloads:2861,totalCrossrefCites:3,totalDimensionsCites:5,hasAltmetrics:0,abstract:null,signatures:"Iztok Fister, Marjan Mernik and Janez Brest",downloadPdfUrl:"/chapter/pdf-download/15613",previewPdfUrl:"/chapter/pdf-preview/15613",authors:[{id:"11259",title:"Dr.",name:"Marjan",surname:"Mernik",slug:"marjan-mernik",fullName:"Marjan Mernik"},{id:"21330",title:"Dr.",name:"Iztok",surname:"Fister",slug:"iztok-fister",fullName:"Iztok Fister"},{id:"22483",title:"Prof",name:"Janez",surname:"Brest",slug:"janez-brest",fullName:"Janez Brest"}],corrections:null},{id:"15614",title:"Linear Evolutionary Algorithm",doi:"10.5772/14969",slug:"linear-evolutionary-algorithm",totalDownloads:2330,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:null,signatures:"Kezong Tang, Xiaojing Yuan, Puchen Liu and Jingyu Yang",downloadPdfUrl:"/chapter/pdf-download/15614",previewPdfUrl:"/chapter/pdf-preview/15614",authors:[{id:"19381",title:"Dr.",name:"ke-zong",surname:"tang",slug:"ke-zong-tang",fullName:"ke-zong tang"}],corrections:null},{id:"15615",title:"Genetic Algorithm Based on Schemata Theory",doi:"10.5772/15927",slug:"genetic-algorithm-based-on-schemata-theory",totalDownloads:2942,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:0,abstract:null,signatures:"Eisuke Kita and Takashi Maruyama",downloadPdfUrl:"/chapter/pdf-download/15615",previewPdfUrl:"/chapter/pdf-preview/15615",authors:[{id:"22506",title:"Prof.",name:"Eisuke",surname:"Kita",slug:"eisuke-kita",fullName:"Eisuke Kita"}],corrections:null},{id:"15616",title:"In Vitro Fertilization Genetic Algorithm",doi:"10.5772/16074",slug:"in-vitro-fertilization-genetic-algorithm",totalDownloads:2280,totalCrossrefCites:0,totalDimensionsCites:6,hasAltmetrics:0,abstract:null,signatures:"Celso G. 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He held the positions of assistant and associate research professor at Hunan Rice Research Institute, China in 2013 and 2017, respectively.",institutionString:"Hunan Agricultural University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Hunan Rice Research Institute",institutionURL:null,country:{name:"China"}}},coeditorThree:{id:"460045",title:"Dr.",name:"Haiming",middleName:null,surname:"Tang",slug:"haiming-tang",fullName:"Haiming Tang",profilePictureURL:"https://intech-files.s3.amazonaws.com/a043Y00000vBvpbQAC/Co1_Profile_Picture__c%202022-03-10%2009%3A05%3A37.552",biography:"Dr. Haiming Tang received his bachelor’s degree in Agronomy at Hunan Agricultural University (HNAU), China in 2002, got his master’s degree in Crop Genetics and Breeding from HNAU in 2005, and obtained his Ph.D. in Crop Science from HNAU in 2008. He held the positions of associate professor and professor at Hunan Soil and Fertilizer Institute, China in 2011 and 2017, respectively.",institutionString:"Soil and Fertilizer Institute of Hunan Province",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Soil and Fertilizer Institute of Hunan Province",institutionURL:null,country:{name:"China"}}},coeditorFour:null,coeditorFive:null,topics:[{id:"5",title:"Agricultural and Biological Sciences",slug:"agricultural-and-biological-sciences"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"466998",firstName:"Dragan",lastName:"Miljak",middleName:"Anton",title:"Mr.",imageUrl:"https://mts.intechopen.com/storage/users/466998/images/21564_n.jpg",email:"dragan@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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The wearable device market is currently having a worldwide profit of around $34 billion and is expected to reach above $50 billion by 2022 owing to wearables’ ease of use, flexibility, and convenience [4]. Real-time monitoring, operational efficiency, and fitness tracking are reported as main factors supporting the market growth of health wearable devices such as smart watches, smart glasses, and other wellness gadgets, with expected $12.1 billion world market by 2021 [5].
\nIn the past decade, the recent progress in developing wearable devices was more focused on monitoring physical parameters, such as motion, respiration rate, etc. [3, 6, 7]. Today, there is a great interest in evolving wearable sensors capable of detecting chemical markers relevant to the status of health. Different approaches have been applied by researchers to design and fabricate wearable biosensors for remote monitoring of metabolites and electrolytes in body fluids including tear, sweat, and saliva [3, 8, 9, 10]. A great example would be the development of small and reliable sensors that would allow continuous glucose monitoring in diabetic patients [11, 12]. Diabetes is a chronic disease that can significantly impact on quality of life and reduce life expectancy. However, diabetics can stay one step ahead of the disease by monitoring their blood glucose level to minimize the complication of the disease by proper administration of insulin. Currently, blood analysis is the gold standard method for measuring the level of glucose in patient’s blood. However, this technique cannot be applied without penetrating the skin, which can be painful and inconvenient, and requires user obedience. Therefore, current research focuses on the development of portable and wearable devices capable of continuous glucose sensing through noninvasive detection techniques.
\nA majority of the recent studies in this field have targeted the area of personalized medicine, endeavoring to develop miniaturized wearable devices featuring real-time glucose monitoring in diabetic patients [12, 13, 14, 15]. One great example is contact lens which is an ideal wearable device that can be worn for hours without any pain or discomfort [16]. Integration of glucose biosensors into contact lenses has recently been demonstrated by several research groups [9, 17, 18]. However, the level of glucose in tear fluid is very low (0.1–0.6 mM), requiring a high sensitivity of the sensor for picking up the signal from expected chemical reaction [3, 19]. Yao et al. [16] have fabricated a contact lens with integrated sensor for continuous tear glucose monitoring with wireless communication system over a distance of several centimeters. The sensor demonstrated a fast response of 20 s with a minimum detection of less than 0.01 mM glucose, which is 10–60 times lower than glucose level in human tear [16].
\nIn addition to glucose, lactate is an important metabolite in the human body, which gets converted into l-lactate under hypoxic condition [20]. l-Lactate levels in tear fluid is about 1–5 mmol L−1, which might increase significantly due to some heath conditions including ischemia, inadequate tissue oxygenation, stroke, and different types of cancer [21]. Thomas et al. [22] demonstrated an invasive detection of lactate in human tear by integrating an amperometric lactate sensor with Pt working (WE) and reference (RE) electrodes as well as a counter electrode (CE) as current drain, on a polymer-based contact lens, measuring lactate in situ in human tears without any need for physical sampling [22].
\nVery recently, Park et al. [17] reported a novel approach for fabricating fully transparent and stretchable smart contact lens capable of wirelessly monitoring the level of glucose in the tears of diabetic patients. Figure 1 shows the layout of fabricated devices made of glucose sensors, wireless circuit, and display pixel on soft and transparent contact lens substrate (Figure 1a and b). The circuit diagram of the device is illustrated in Figure 1a, with radio frequency antenna receiving signals from a transmitter and a rectifier converting the signals to DC (Figure 1a and c). A continuous network of ultralong Ag nanofibers was used as stretchable electrodes for the antenna and interconnects (Figure 1d). In the case of any change in the concentration of glucose in tear, the sensor resistance changes resulting in the light-emitting diode (LED) pixel turning on or off. The device was tested in vitro using a live rabbit, providing substantial finding for smart contact lenses as one of the promising wearable devices in healthcare system [17].
\n(a) (i) Schematic illustration and (ii) operation of the soft, smart contact lens and (iii) the circuit diagram of the smart contact lens system. The soft, smart contact lens is composed of (b) a hybrid substrate; (c) functional devices including rectifier, LED, and glucose sensor; and (d) a transparent, stretchable conductor for antenna and interconnects [
In addition to tear, sweat electrolyte concentrations and blood serum are related [2, 8]. As one of the most readily accessible human biofluids, a great deal of information about the human body and its physical performance could be obtained via monitoring sweat electrolyte concentrations [23, 24]. Several groups have reported the key biomarkers in human sweat (e.g., sodium level, pH change, lactate concentration) relevant to human health and well-being, for monitoring athletic performance during sporting activities [25]. Jia et al. fabricated a skin-worn tattoo-based sensor for real-time monitoring of lactate in human sweat, offering substantial benefits for biomedical as well as sport applications [25]. In another approach, Curto et al. [26] fabricated a wearable and flexible microfluidic platform capable of monitoring changes in the sweat pH in real time. Anastasova et al. [27] developed a flexible microfluidic device for real-time monitoring of metabolite such as lactate as well as electrolytes such as pH and sodium in human sweat. Recently, Gao et al. [28] developed a flexible and wearable device (Figure 2) made of arrays of sensors for real-time monitoring of heavy metals, such as Zn, Cu, and Hg in human sweat. The device fabrication method is presented in Figure 2a, showing the deposition and stripping steps on microelectrodes. The sensing mechanism was based on an electrochemical detection of targeted heavy metals through four microelectrodes, including Au and Bi working electrodes, Ag reference electrode, and an Au counter electrode (Figure 2b and c). The fabricated device demonstrated high stability and selectivity toward heavy metals, providing a great platform to advancing the field of wearable biosensors for healthcare application, via monitoring the level of some heavy metals in human sweat [28]. A balanced level of Zn is necessary in the human body as a low and high Zn concentration can lead to pneumonia and liver damages, respectively [29, 30]. High level of Cu in the human body can lead to several diseases including Wilson’s disease and heart, kidney, and liver failures as well as brain diseases [31, 32]. The fabricated device demonstrated high stability and selectivity toward heavy metals, providing a great platform to advancing the field of wearable biosensors for healthcare application [28].
\n(a) A schematic showing the concept of deposition and stripping on microelectrodes. (b) A schematic showing the composition of the microsensor array. (c) Optical image of a flexible sensor array interfacing with a flexible printed circuit connector [
Saliva, as a great diagnostic fluid, can be used in personal health devices for real-time monitoring of chemical markers including salivary lactate analysis [33]. Chai et al. developed a saliva nanosensor with a radio-frequency identification tag, integrated into dental implants for detecting cardiac biomarkers in saliva and predicting close heart attack in patients suffering from cardiovascular diseases [34]. In another approach, an instrumented mouthguard was designed and fabricated by Kim et al. [35] for measuring salivary uric acid levels which could be a biomarker for several diseases including hyperuricemia, gout, physical stress, and renal syndrome. The fabricated device showed high selectivity and sensitivity to low level of uric acid as well as great stability during a 4-h operation period [35]. Mannoor et al. [36] developed a hybrid biosensor made of graphene layers printed onto water-soluble silk, for noninvasive detection of bacteria through body fluids including sweat and saliva. This graphene/silk hybrid device illustrated an extremely high sensitivity to bacteria in body fluid with detection limits down to a single bacterium [36]. In addition, the fabricated device provided the potential users with battery-free operation and wireless communication system via radio frequency [36]. Arakawa et al. [37] designed and fabricated a salivary sensor equipped with a wireless measurement system, embedded onto a mouthguard support, featuring a high sensitivity toward detection of glucose over a range of 5–1000 μmol L−1. The device demonstrated a great stability during a 5-h real-time glucose monitoring period in an artificial saliva with a phantom jaw [37]. In a similar approach, de Castro et al. [38] developed a microfluidic paper-based device integrated into a mouthguard, for continues monitoring of glucose and nitrite in human saliva. The saliva samples were collected from periodontitis and/or diabetes patients as well as healthy individuals. The fabricated device featured a low detection limit of 27 and 7 μmol L−1 for glucose and nitrite, respectively [38].
\nIn summary, there is a great potential for micro- and nanosensors’ integration into healthcare monitoring devices, developing new technologies for noninvasive detection of diseases in the human body. Flexible wearable devices offer promising capabilities in real-time monitoring of body fluids including tear, sweat, and saliva. However, more research is required to expand the use of wearable platforms in continuous analysis of body fluids, providing reliable real-time detection of targeting ions and proteins, among other complex analytes.
\nIn the Western world, the leading cause of death is cardiovascular diseases. Even if the knowledge acquired in cardiology is great, the heart has not yet revealed all its secrets. However, doctors have many ways to study and verify its proper functioning. In particular, they use cardiac signals, the electrocardiogram (ECG) and the phonocardiogram (PCG) which are an important tools in the diagnosis of cardiac pathologies.
The ECG is the signal reflecting the recording of the bioelectrical activities of the cardiac system. It is rich in information on the functional aspects of the heart and the cardiovascular system.
The electrocardiogram includes three important waves called the P wave, complex QRS and T wave which translate respectively the atrial activity, the ventricular activity and ventricular repolarization. From these waves are determined intervals known by the PR interval which defines the atrioventricular conduction time, the ST segment which corresponds to the ventricular repolarization phase, a phase during which the ventricular cells are all depolarized, and the RR interval which indicates the cardiac period, i.e. the time between two successive beats. Inverting it, we get then the heart rate commonly expressed in beats per minute.
The QT interval reflects all ventricular activity, i.e. phases of depolarization and repolarization. The time intervals between these different ECG waves provide important indicators for the diagnosis of heart disease because they reflect physiological processes of the heart and autonomic nervous system [1, 2, 3].
The analysis of these different intervals often involves the study of their variability.
At the level of the PCG signal, this signal produces two noises (S1 and S2) during the opening and closing of the valves under normal conditions. Two other noises (S3 and S4) with significantly lower amplitudes than the first two sometimes appear at the level of the cardiac cycle due to the effect of pathology or age [4].
The S1 sound occurs just after the onset of systole and is preferentially due to the closure of the atrioventricular valves. The S2 sound is produced at the beginning of diastole and is due to the closure of the aortic and pulmonary valves. However, doctors use heart auscultation to hear two normal sounds S1 and S2 using a medical instrument called a stethoscope. Also, cardiac synchronization can simultaneously gives the two physiological signals ECG and PCG, such that the S1 noise appears at the end of the R peak and the S2 noise at the end of the ECG segment, as for the S3 and S4 noises, they originate respectively at the end of the P wave and in the middle of the diastolic phase of the electrocardiogram (Figure 1).
Synchronization between ECG and PCG signal.
Generally, the recording conditions of the ECG and PCG make that the signals are necessarily noisy by processes other than cardiac. These artifacts can be of physiological origin (skin, muscle, breathing…) or environmental (mains current, electromagnetic artifacts, placement of the electrode …).
The practitioner who analyses the ECG can then be discomfort by the presence of noise: in the case where, for example, he looks for the existence of a normal sinus rhythm and he is looking for the presence of the P wave preceding the R wave, the P wave, which is of low amplitude, can be drowned in noise. In the same way, a strong variation of the base line can prevent discerning an anomaly of the over- or under-shift type of the S-T segment, for example. To be able effectively segment heartbeats without altering clinical information, a certain number of pre-treatments are necessary. The purpose of this step is attenuate, or at by eliminates noises present in the raw ECG signal such as baseline variations or sector the interference at 50 Hz. Also, the doctor finds it difficult to listen to the S1 and S2 heart sounds due to the presence of heart murmurs and this prevents the doctor from diagnosing the patient.
These heart murmurs are an additional noise; it was produced by a turbulent circulation of blood toward the heart. In fact the objective is to filter the non-stationary ECG and PCG signals and the extraction useful clinical information is found in the time intervals defined by the ECG waves characteristic, including the P wave, QRS complex, T wave, PR interval, ST segment, and interval QT, the defined time intervals between two characteristics ECG waves provide important indicators for the diagnosis of heart disease because they reflect physiological processes.
However, it is clear that to achieve this study, it is essential to perform a pre-processing of the ECG and PCG signals in order to then detect the different waves of the ECG signal.
In this article the morphological transform is used to remove noise and to detect the characteristics of the ECG and PCG signal.
This transformation uses mathematical morphology to realize, in particular the morphological filtering and the top hat transform. Mathematical morphology, based on set operations, provides an approach to developing nonlinear signal processing methods in which the shape of a signal’s information is incorporated [5]. In these operations, the result of one set of data transformed by another set depends on the shapes of the two sets involved. A structuring element must be designed according to the shape characteristics of the signal that must be extracted. There are two basic morphological operators: erosion and dilation. Opening and closing are derived operators defined in terms of erosion and dilation [6].
Dilation reduces the peaks in a signal and to widen the valleys, erosion fills in the valleys and thickens the peaks in the signal; opening removes the peaks but preserves the valleys, and closing fills in the valleys, removes the wells (or valleys). The “closing” and “opening” operators behave like filters; we will speak of “Morphological Filter” [7].
An important number of researches work using different tools and methods of noise filtering have been presented in the literature. The methods often based on classical linear high-pass filtering, low-pass or band-pass [8, 9, 10], linear adaptive filtering [11], filtering based on neural networks [12, 13, 14, 15], have been proposed to eliminate noise affecting the line of basis of the ECG signal. The major disadvantage of these methods is the distortion of the signal due to the overlapping of the spectra of the ECG, PCG and their noises. On the other hand, a large number of methods have been proposed for the detection of ECG signal waves [12, 13, 14, 15, 16, 17, 18, 19, 20]. The majority of these methods are based on adaptive filtering or thresholding, which shows the limitation of the application. The emergence of treatment method in the non-stationary case has helped the researchers to develop new tools better suited to filtering. Techniques based on the wavelet theory have already proved their worth for the filtering of noise from the ECG signal. Donoho and Johnston proposed a denoising method by thresholding of wavelet [21, 22]. The denoising method by wavelet thresholding was treated the wavelet coefficients by a threshold which must be chosen in advance. Approaches for estimate the value of this threshold can be found in [23, 24].
In this chapter, the pre-processing is realized in two stages, a stage of the correction of the line base by Morphological filtering and the top-hat transform for remove noises that are based on mathematical operators called derivation operators opening and closing morphology. Followed by the second step which is consisted of detecting the waves of the ECG signal and the cardiac murmurs of the PCG signal by morphology operators and a multi-scale structuring element.
The morphological transform is very widespread in the domain of signal processing and image processing because of its robustness and its simple and fast calculation.
[25, 26]. Mathematical morphology, based on set operations, provides an approach to the development of nonlinear methods of signal processing, in which the form of a signal’s information is incorporated [27]. In these operations, the result of a data set transformed by another set depends on the shapes of both sets involved. A structuring element must be designed according to the characteristics of shape of the signal to be extracted.
There are two basic morphological operators: erosion
Opening and closing are derived operators defined in terms of erosion and dilation.
[28]. These operators are described in detail below with the corresponding mathematical expressions. Throughout this document denotes the discrete ECG signal of point size and the symmetrical structuring element of M points.
a. Erosion.
To obtain the eroded function of f(x), we attribute to f(x) its minimum value in the domain of the structuring element B and this, at each new displacement of B (Figure 2). The following formula illustrates the erosion of the function f(x) (original signal) by a structuring element
b. Dilation.
a) Eroded ECG signal. b) Dilated ECG signal.
To obtain the dilated function of
Erosion shrinks peaks and the crest lines. The peaks narrower than the element structuring disappear. At the same time, it widens the valleys and the minima [29].
The dilation produces the opposite effects (fills in the valleys and thickens the peaks).
c. Opening.
As in mathematical morphology, the opening consists of the erosion followed by dilation. The opening of
a) Opening ECG signal. b) Closing ECG signal.
The opening removes the peaks but preserves the valleys [30], according to the equation:
d. Closing.
As in mathematical morphology, closing consists of dilation followed by erosion (Figure 3). The closing of
The closing fills the valleys [32] as follows:
The “closing” and “opening” operators behave like filters; these are in the same time morphological Filters [33].
The opening and closing by adjunction create a simpler function than the initial function, by softening the latter in a nonlinear manner.
Opening (closing) eliminates positive (negative) peaks respectively that are narrower than the structuring element.
The opening (the closing) is located below (above) the initial function.
e. Structuring element.
After the selection of the morphology operator, the structuring element (SE) is the next component of the morphological analysis to be defined. Generally, only when the shape of the signal matches those of the structuring element that the signal can be preserved. Therefore, the shape, length (domain) and size (amplitude) of the structuring element should be chosen according to the signal to be analyzed. The shapes of the structuring element can vary regularly or irregularly, such as a triangle, line (flat), or a semicircle.
In signal processing, the term “filter” is not very precise, it depends on the context in which it is used. It sometimes implies convolution, sometimes also any operation that produces a new function. On the contrary, mathematical morphology defines it very precisely [34, 35, 36]:
Any increasing and idempotent transformation on a trellis defines a morphological filter.
Increase:
This hypothesis is the most fundamental. It ensures that the basic structure of the trellis, i.e. the order relation, is preserved during a morphological filtering.
This property causes the filter to generally lose information.
Idempotence:
By definition, an idempotent transformation transforms the signal into an invariant.
This property often appears, but implicitly, in the descriptions. We say of an optical filter that it is red, or of an amp that its bandwidth is 50 kHz. Here, we will pose it as an axiom.
Idempotence is reached either after a single pass or as a limit by iteration. More generally, a sequence of operations, taken as a whole, can be idempotent.
Finally, note that when linear filters are idempotent, then they do not admit an inverse: they lose information, which brings them near to morphological filters.
In practice, operators morphologic are based on different application scenarios in signal processing [37, 38, 39, 40, 41, 42]. Sometimes it is difficult to obtain prior knowledge of the positive (positive peak) or negative (negative peak) pulse characteristics of the signal, especially when both positive and negative pulses are used. We can make by the combination of the four operators an average filter presented by the following formula:
Figure 4 illustrates the results obtained not used to flatten the positive and negative peaks.
a) Opening signal (lime draw
The concept of Top-Hat, due to F. Meyer, is a residue intended to eliminate the slow variations of the signal, or to amplify the contrasts. It therefore applies mainly to functions (Figure 5).
Opening and top hat.
We call Top-Hat the residual between the identity and an invariant opening under vertical translation [43]:
We define in the same way a dual top-hat, residue between a closure and the identity:
Multi-scale erosion and dilation are defined by:
and
The original purpose of multi-scale morphology analysis is based on the morphology composition of the structuring element g is to improve the speed of morphology analysis by a large scale of structuring element and to expand the domains of application in signal processing.
The original purpose of multi-scale morphology analysis is based on the morphology composition of the structuring element g is to improve the speed of morphology analysis by a large scale of structuring element and to expand the domains of application in signal processing.
The opening and closing operators proposed in this work for ECG signal processing, is shown in Figure 6 below.
Steps of the morphological filter algorithm.
It consists of different phases. A first phase which consists in detecting variations in the baseline from the original noisy ECG signal. A second phase which consists in correcting these variations (correction of the baseline), and a third phase which consists in suppressing the remaining noises to finally generate the filtered ECG signal.
These different phases are realized through the development of a sequence of opening and closing operators.
This sequence is based on exploiting the different characteristics of baseline drift and noise contamination in ECG signals, different structuring elements and different morphological operators. For baseline correction, an opening operator followed by a closing operator is defined; as well as noise cancelation. They are described in detail in the following subsections.
To correct for baseline variations, the variations of that line (
The signal
The approach adopted for noise suppression appeal of Top-hat transformations, which are translated by the equations below.
Figure 7 represents the block diagram describing the structure of the top-hat transformation for noise suppression.
Diagram of PCG filtering.
It consists of three steps: The first concerns the acquisition of ECG signals (
This step is followed by another step that allows noise removal. This step uses the morphology operators defined in Eq. (12).
The proposed algorithm is implemented under MATLABR14 environment. It is tested on a set of ECG signals (noisy) from the MIT-BIH database [47].
Figure 7 below illustrates the stages of noise suppression and heart murmurs.
The first step is to normalize the PCG input signal. A second step is to remove noises, and a third step is to remove heart murmurs.
The original signal has been normalized before performing any operation. The PCG signal is re-sampled at 8000 Hz with 16 bits of precision and converted to WAVE format and normalized by:
The aim of normalization is to reduce the amplitudes of the PCG signal.
Noise suppression uses the morphological filter, which is presented by the following equations:
The filter applied for the suppression of murmurs is the average filter; it is described in the equation below.
The detection of murmurs is based on two morphological operators, namely closing and opening, to suppress peaks. The average between the closing and opening operator gives the result
The detection of the RR interval can be accomplished only after a good detection of the R peak. This detection goes through three stages. A step which allows locating the positive peaks R by the opening operation and another step which allows locating the negative peaks R by the application of the closing operation. The final step to arrive at these peaks and valleys is the subtraction of the filtered ECG signal f with the two previous operations.
The following formula illustrates the extraction of R positive peaks:
And the following formula illustrates the extraction of valleys or negative peaks R:
Formula (18) and (19) are equivalent to:
Structuring element B is used to detect peaks and valleys. In this case it is considered as a geometric shape “horizontal segment of different lengths”. The following formula shows the:
where
One of the problems of the morphological approach is to determine the optimal value of
After detecting the RR rhythm, the next step is to detect the T wave. It uses the erosion operator to build maximum thresholding. Knowing that the amplitude of the T wave is enormously greater than the Q wave and the S wave in the normal or abnormal case of the ECG signal.
The following formula illustrates the detection of the T wave:
Where the sets f and B are underlined by
The next phase is the detection of the Q and S waves of the ECG signal. It uses a morphological operator called closing to detect the negative peaks. On the other hand, the morphology of Q and S waves in an ECG signal are of negative amplitudes. For this, we have chosen the most adapted closing operator to detect the negative peaks. Finally, the detection of the P wave is based on the opening operator which is combined with a structuring element of multi-scale, according to the equation:
The signal is operated by two successive opening operators with a structuring element of an equal scale 2. This means that the number of opening operations and the number of the structuring element is two scales.
The proposed morphological approach for baseline correction and noise suppression in the ECG signal was tested by the use of the MIT-BIH arrhythmia database.
Figure 8 illustrate respectively the noisy ECG signal, the ECG signal after baseline correction and the resulting filtered ECG signal.
a) Original ECG. b) Baseline correction. c) Filtered signal.
After acquiring the ECG signal, the next step is baseline correction. It consists of the application of morphological operations: “opening and closing”.
The signal is first opened by a structuring element
The structuring element
Figure 9 shows the closing operation which uses a structuring element to remove the valleys left by the opening operation. The length of the structuring element
Closing effect (to the left) and the opening operator (to the right).
The ECG signal, the most characteristic waves are the P wave, the T wave and the QRS complex, which are generally less than 0.2 second.
Therefore,
Since we employ
The final step to arrive at the baseline correction is the subtraction of the noisy ECG signal
After baseline correction, the next step is noise removal. It consists of the application of morphology operators of the morphological transformation by top hat.
In fact, the input signal
The morphological transformation by Hat-Top permits to extract the positive and negative impulses simultaneously by the application of the operations of opening and closing.
It should be noted that the shape of the structuring element in the noise suppression is different compared to the baseline correction. Indeed, it can take two different shapes and of equal lengths: a triangular shape
In our case, the size of the structuring element was fixed at 5 samples, with the value of the structuring element of
The algorithm is applied respectively to records 209 and 234 of the MIT-BIH Arrhythmia database. Figures 10 and 11 illustrate, that the filtered ECG signal does not present any variation of the base line, also the different waves of the signal are clearly highlighted, and without any deformation.
a) Original ECG (record 234), b) filtered signal.
a) Original ECG (record 209). b) Filtered signal.
The proposed morphological approach for noise suppression and detection of heart murmurs from the PCG signal was tested from the Pascal Classifying Heart Sound Challenge [49].
Figure 12, shows a noisy signal that has been filtered by the morphological filter. This filter uses two successive operators including closing and opening.
Noise suppression of PCG signal.
These operators are combined with a single structuring element
In this context, the length
It depends on the duration of heart sounds S1 and S2 which are basic frequency (0.1–0.15) second, (70–0.14) ms, respectively.
After noise suppression, the next step is heart murmur suppression. It uses an average filter, which is combined with a structuring element
Knowing that heart murmurs are a frequency content above 100 Hz. Starting from this hypothesis, the length
Figure 13 below shows heart murmur suppression.
Murmurs detection of PCG signal.
The proposed morphological approach for detecting the beginnings and endings of QRS complexes, the T wave and the P wave of the ECG signal were tested from the MIT-BIH arrhythmia database.
For each (filtered) ECG input signal, the following procedures were performed:
(a) pre-processing the ECG signal; (b) detecting the RR heart rate by the morphological filter; (c) detection of the T wave by maxima of the erosion operator; (d) detection of the Q and S waves of the ECG signal by the closure operator; (e) the detection of the P wave is detected by the opening operator with a multi-scale structuring element.
Figures 14 to 16 illustrate the results obtained on three different recording representing different morphologies where the power of the morphological transformation algorithm is clearly shown.
Detection results (record 102).
Detection results (record 103).
Detection results (record 113).
The characteristic waves of an electrocardiogram (ECG) signal and the heart sounds of the phonocardiogram (PCG) signal provide important indicators for the diagnosis of heart disease; they reflect physiological processes of the heart and autonomic nervous system. The analysis and interpretation of these physiological signals make it possible to highlight new phenomena, which is sometimes possible to explain at the physiological level, and which leads to a better understanding of the overall functioning of the heart.
The automatic analysis of ECG and PCG signals provides the cardiologist with the information needed to diagnose cardiac pathologies. The implementation of reliable algorithms for the processing of ECG and PCG signals, making it possible to detect the useful information carried by the ECG and PCG signals remains a major concern for technicians.
A set of algorithms using morphology transforms has been developed. These algorithms concerning:
On the one hand the pre-processing of ECG and PCG signals where an algorithm has been developed and implemented: one for the elimination of baseline ripples and the other for noise suppression.
and on the other hand, the analysis of ECG and PCG signals where an algorithm has been developed for the detection of QRS complexes, the T wave, the P wave of the ECG signal and the murmurs of the PCG signal.
The algorithms were evaluated by applying them to ECG and PCG signals from the universal database ‘MIT-BIH’ and Dataset from “Pascal Classifying Heart Sound Challenge, respectively.
Morphological filtering which uses two morphological operators opening and closing for the correction of the baseline.
In noise suppression, the Top Hat transformation was used. It combines the subtraction of the closing and opening morphology operators.
For the detection of ECG signal parameters, typically the QRS complex, the T wave, and the P wave, two techniques have been presented which are called multi-scale morphology and morphological operators.
At the PCG signal level, we used a morphological filter for noise suppression and heart murmur detection.
These techniques, which are based on mathematical morphology, are very effective in estimating rapid changes in the morphology of ECG and PCG signals.
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Integrity - We are consistent and dependable, always striving for precision and accuracy in the true spirit of science.
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\n\nDisruptiveness - We are eager for discovery, for new ideas and for progression. We approach our work with creativity and determination, with a clear vision that drives us forward. We look beyond today and strive for a better tomorrow.
\n\nIntechOpen is a dynamic, vibrant company, where exceptional people are achieving great things. We offer a creative, dedicated, committed, and passionate environment but never lose sight of the fact that science and discovery is exciting and rewarding. We constantly strive to ensure that members of our community can work, travel, meet world-renowned researchers and grow their own career and develop their own experiences.
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At the beginning of humification, the significant decrease in the intensity of the band located at 1735 cm–1 shows that lignin is affected at the first stage of the composting process. At the end of the humification, the band located toward 3450–3420 cm–1 at the beginning of the process undergoes a systematic shift (Δν of the order of 10 cm–1) toward lower wave numbers. The band located at 1660–1650 cm–1 on the Fourier transform infrared spectroscopy (FTIR) spectra before composting shifts systematically toward 1640 cm–1 at the end of humification. This phenomenon can be used as index of compost maturity. 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He received his medical degree from the Sousse Faculty of Medicine at Sousse, University of Sousse, Tunisia. He completed his surgical residency in General Surgery at the University Hospital Farhat Hached of Sousse and was a member of the Unit of Liver Transplantation in the University of Rennes, France. He then worked in the Department of Surgery at the Sahloul University Hospital in Sousse. Professor Derbel is presently working at the Clinique les Oliviers, Sousse, Tunisia. His hospital activities are mostly concerned with laparoscopic, colorectal, pancreatic, hepatobiliary, and gastric surgery. He is also very interested in hernia surgery and performs ventral hernia repairs and inguinal hernia repairs. He has been a member of the GREPA and Tunisian Hernia Society (THS). During his residency, he managed patients suffering from diabetic foot, and he was very interested in this pathology. For this reason, he decided to coordinate a book project dealing with the diabetic foot. Professor Derbel has published many articles in journals and collaborates intensively with IntechOpen Access Publisher as an editor.",institutionString:"Clinique les Oliviers",institution:null},{id:"300144",title:"Dr.",name:"Meriem",middleName:null,surname:"Braiki",slug:"meriem-braiki",fullName:"Meriem Braiki",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/300144/images/system/300144.jpg",biography:"Dr. Meriem Braiki is a specialist in pediatric surgeon from Tunisia. She was born in 1985. She received her medical degree from the University of Medicine at Sousse, Tunisia. She achieved her surgical residency training periods in Pediatric Surgery departments at University Hospitals in Monastir, Tunis and France.\r\nShe is currently working at the Pediatric surgery department, Sidi Bouzid Hospital, Tunisia. Her hospital activities are mostly concerned with laparoscopic, parietal, urological and digestive surgery. She has published several articles in diffrent journals.",institutionString:"Sidi Bouzid Regional Hospital",institution:null},{id:"229481",title:"Dr.",name:"Erika M.",middleName:"Martins",surname:"de Carvalho",slug:"erika-m.-de-carvalho",fullName:"Erika M. de Carvalho",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229481/images/6397_n.jpg",biography:null,institutionString:null,institution:{name:"Oswaldo Cruz Foundation",country:{name:"Brazil"}}},{id:"186537",title:"Prof.",name:"Tonay",middleName:null,surname:"Inceboz",slug:"tonay-inceboz",fullName:"Tonay Inceboz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/186537/images/system/186537.jfif",biography:"I was graduated from Ege University of Medical Faculty (Turkey) in 1988 and completed his Med. PhD degree in Medical Parasitology at the same university. I became an Associate Professor in 2008 and Professor in 2014. I am currently working as a Professor at the Department of Medical Parasitology at Dokuz Eylul University, Izmir, Turkey.\n\nI have given many lectures, presentations in different academic meetings. I have more than 60 articles in peer-reviewed journals, 18 book chapters, 1 book editorship.\n\nMy research interests are Echinococcus granulosus, Echinococcus multilocularis (diagnosis, life cycle, in vitro and in vivo cultivation), and Trichomonas vaginalis (diagnosis, PCR, and in vitro cultivation).",institutionString:"Dokuz Eylül University",institution:{name:"Dokuz Eylül University",country:{name:"Turkey"}}},{id:"71812",title:"Prof.",name:"Hanem Fathy",middleName:"Fathy",surname:"Khater",slug:"hanem-fathy-khater",fullName:"Hanem Fathy Khater",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/71812/images/1167_n.jpg",biography:"Prof. Khater is a Professor of Parasitology at Benha University, Egypt. She studied for her doctoral degree, at the Department of Entomology, College of Agriculture, Food and Natural Resources, University of Missouri, Columbia, USA. She has completed her Ph.D. degrees in Parasitology in Egypt, from where she got the award for “the best scientific Ph.D. dissertation”. She worked at the School of Biological Sciences, Bristol, England, the UK in controlling insects of medical and veterinary importance as a grant from Newton Mosharafa, the British Council. Her research is focused on searching of pesticides against mosquitoes, house flies, lice, green bottle fly, camel nasal botfly, soft and hard ticks, mites, and the diamondback moth as well as control of several parasites using safe and natural materials to avoid drug resistances and environmental contamination.",institutionString:null,institution:{name:"Banha University",country:{name:"Egypt"}}},{id:"99780",title:"Prof.",name:"Omolade",middleName:"Olayinka",surname:"Okwa",slug:"omolade-okwa",fullName:"Omolade Okwa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/99780/images/system/99780.jpg",biography:"Omolade Olayinka Okwa is presently a Professor of Parasitology at Lagos State University, Nigeria. She has a PhD in Parasitology (1997), an MSc in Cellular Parasitology (1992), and a BSc (Hons) Zoology (1990) all from the University of Ibadan, Nigeria. She teaches parasitology at the undergraduate and postgraduate levels. She was a recipient of a Commonwealth fellowship supported by British Council tenable at the Centre for Entomology and Parasitology (CAEP), Keele University, United Kingdom between 2004 and 2005. She was awarded an Honorary Visiting Research Fellow at the same university from 2005 to 2007. \nShe has been an external examiner to the Department of Veterinary Microbiology and Parasitology, University of Ibadan, MSc programme between 2010 and 2012. She is a member of the Nigerian Society of Experimental Biology (NISEB), Parasitology and Public Health Society of Nigeria (PPSN), Science Association of Nigeria (SAN), Zoological Society of Nigeria (ZSN), and is Vice Chairperson of the Organisation of Women in Science (OWSG), LASU chapter. She served as Head of Department of Zoology and Environmental Biology, Lagos State University from 2007 to 2010 and 2014 to 2016. She is a reviewer for several local and international journals such as Unilag Journal of Science, Libyan Journal of Medicine, Journal of Medicine and Medical Sciences, and Annual Research and Review in Science. \nShe has authored 45 scientific research publications in local and international journals, 8 scientific reviews, 4 books, and 3 book chapters, which includes the books “Malaria Parasites” and “Malaria” which are IntechOpen access publications.",institutionString:"Lagos State University",institution:{name:"Lagos State University",country:{name:"Nigeria"}}},{id:"273100",title:"Dr.",name:"Vijay",middleName:null,surname:"Gayam",slug:"vijay-gayam",fullName:"Vijay Gayam",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/273100/images/system/273100.jpeg",biography:"Dr. Vijay Bhaskar Reddy Gayam is currently practicing as an internist at Interfaith Medical Center in Brooklyn, New York, USA. He is also a Clinical Assistant Professor at the SUNY Downstate University Hospital and Adjunct Professor of Medicine at the American University of Antigua. He is a holder of an M.B.B.S. degree bestowed to him by Osmania Medical College and received his M.D. at Interfaith Medical Center. His career goals thus far have heavily focused on direct patient care, medical education, and clinical research. He currently serves in two leadership capacities; Assistant Program Director of Medicine at Interfaith Medical Center and as a Councilor for the American\r\nFederation for Medical Research. As a true academician and researcher, he has more than 50 papers indexed in international peer-reviewed journals. He has also presented numerous papers in multiple national and international scientific conferences. His areas of research interest include general internal medicine, gastroenterology and hepatology. He serves as an editor, editorial board member and reviewer for multiple international journals. His research on Hepatitis C has been very successful and has led to multiple research awards, including the 'Equity in Prevention and Treatment Award” from the New York Department of Health Viral Hepatitis Symposium (2018) and the 'Presidential Poster Award” awarded to him by the American College of Gastroenterology (2018). He was also awarded 'Outstanding Clinician in General Medicine” by Venus International Foundation for his extensive research expertise and services, perform over and above the standard expected in the advancement of healthcare, patient safety and quality of care.",institutionString:"Interfaith Medical Center",institution:{name:"Interfaith Medical Center",country:{name:"United States of America"}}},{id:"93517",title:"Dr.",name:"Clement",middleName:"Adebajo",surname:"Meseko",slug:"clement-meseko",fullName:"Clement Meseko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/93517/images/system/93517.jpg",biography:"Dr. Clement Meseko obtained DVM and PhD degree in Veterinary Medicine and Virology respectively. He has worked for over 20 years in both private and public sectors including the academia, contributing to knowledge and control of infectious disease. Through the application of epidemiological skill, classical and molecular virological skills, he investigates viruses of economic and public health importance for the mitigation of the negative impact on people, animal and the environment in the context of Onehealth. \r\nDr. Meseko’s field experience on animal and zoonotic diseases and pathogen dynamics at the human-animal interface over the years shaped his carrier in research and scientific inquiries. He has been part of the investigation of Highly Pathogenic Avian Influenza incursions in sub Saharan Africa and monitors swine Influenza (Pandemic influenza Virus) agro-ecology and potential for interspecies transmission. He has authored and reviewed a number of journal articles and book chapters.",institutionString:"National Veterinary Research Institute",institution:{name:"National Veterinary Research Institute",country:{name:"Nigeria"}}},{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",slug:"shailendra-k.-saxena",fullName:"Shailendra K. Saxena",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",biography:"Professor Dr. Shailendra K. Saxena is a vice dean and professor at King George's Medical University, Lucknow, India. His research interests involve understanding the molecular mechanisms of host defense during human viral infections and developing new predictive, preventive, and therapeutic strategies for them using Japanese encephalitis virus (JEV), HIV, and emerging viruses as a model via stem cell and cell culture technologies. His research work has been published in various high-impact factor journals (Science, PNAS, Nature Medicine) with a high number of citations. He has received many awards and honors in India and abroad including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. Dr. Saxena is a fellow of various international societies/academies including the Royal College of Pathologists, United Kingdom; Royal Society of Medicine, London; Royal Society of Biology, United Kingdom; Royal Society of Chemistry, London; and Academy of Translational Medicine Professionals, Austria. He was named a Global Leader in Science by The Scientist. He is also an international opinion leader/expert in vaccination for Japanese encephalitis by IPIC (UK).",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",country:{name:"India"}}},{id:"94928",title:"Dr.",name:"Takuo",middleName:null,surname:"Mizukami",slug:"takuo-mizukami",fullName:"Takuo Mizukami",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94928/images/6402_n.jpg",biography:null,institutionString:null,institution:{name:"National Institute of Infectious Diseases",country:{name:"Japan"}}},{id:"233433",title:"Dr.",name:"Yulia",middleName:null,surname:"Desheva",slug:"yulia-desheva",fullName:"Yulia Desheva",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/233433/images/system/233433.png",biography:"Dr. Yulia Desheva is a leading researcher at the Institute of Experimental Medicine, St. Petersburg, Russia. She is a professor in the Stomatology Faculty, St. Petersburg State University. She has expertise in the development and evaluation of a wide range of live mucosal vaccines against influenza and bacterial complications. Her research interests include immunity against influenza and COVID-19 and the development of immunization schemes for high-risk individuals.",institutionString:'Federal State Budgetary Scientific Institution "Institute of Experimental Medicine"',institution:null},{id:"238958",title:"Mr.",name:"Atamjit",middleName:null,surname:"Singh",slug:"atamjit-singh",fullName:"Atamjit Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/238958/images/6575_n.jpg",biography:null,institutionString:null,institution:null},{id:"252058",title:"M.Sc.",name:"Juan",middleName:null,surname:"Sulca",slug:"juan-sulca",fullName:"Juan Sulca",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252058/images/12834_n.jpg",biography:null,institutionString:null,institution:null},{id:"191392",title:"Dr.",name:"Marimuthu",middleName:null,surname:"Govindarajan",slug:"marimuthu-govindarajan",fullName:"Marimuthu Govindarajan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/191392/images/5828_n.jpg",biography:"Dr. M. Govindarajan completed his BSc degree in Zoology at Government Arts College (Autonomous), Kumbakonam, and MSc, MPhil, and PhD degrees at Annamalai University, Annamalai Nagar, Tamil Nadu, India. He is serving as an assistant professor at the Department of Zoology, Annamalai University. His research interests include isolation, identification, and characterization of biologically active molecules from plants and microbes. He has identified more than 20 pure compounds with high mosquitocidal activity and also conducted high-quality research on photochemistry and nanosynthesis. He has published more than 150 studies in journals with impact factor and 2 books in Lambert Academic Publishing, Germany. He serves as an editorial board member in various national and international scientific journals.",institutionString:null,institution:null},{id:"274660",title:"Dr.",name:"Damodar",middleName:null,surname:"Paudel",slug:"damodar-paudel",fullName:"Damodar Paudel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/274660/images/8176_n.jpg",biography:"I am DrDamodar Paudel,currently working as consultant Physician in Nepal police Hospital.",institutionString:null,institution:null},{id:"241562",title:"Dr.",name:"Melvin",middleName:null,surname:"Sanicas",slug:"melvin-sanicas",fullName:"Melvin Sanicas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241562/images/6699_n.jpg",biography:null,institutionString:null,institution:null},{id:"117248",title:"Dr.",name:"Andrew",middleName:null,surname:"Macnab",slug:"andrew-macnab",fullName:"Andrew Macnab",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of British Columbia",country:{name:"Canada"}}},{id:"322007",title:"Dr.",name:"Maria Elizbeth",middleName:null,surname:"Alvarez-Sánchez",slug:"maria-elizbeth-alvarez-sanchez",fullName:"Maria Elizbeth Alvarez-Sánchez",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",country:{name:"Mexico"}}},{id:"337443",title:"Dr.",name:"Juan",middleName:null,surname:"A. 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The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. The considerable development of technology, including the computing power of computers, is also conducive to the development of bioinformatics, including personalized medicine. In an era of rapidly growing data volumes and ever lower costs of generating, storing and computing data, personalized medicine holds great promises. Modern computational methods used as bioinformatics tools can integrate multi-scale, multi-modal and longitudinal patient data to create even more effective and safer therapy and disease prevention methods. Main aspects of the topic are: Applying bioinformatics in drug discovery and development; Bioinformatics in clinical diagnostics (genetic variants that act as markers for a condition or a disease); Blockchain and Artificial Intelligence/Machine Learning in personalized medicine; Customize disease-prevention strategies in personalized medicine; Big data analysis in personalized medicine; Translating stratification algorithms into clinical practice of personalized medicine.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/7.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11403,editor:{id:"351533",title:"Dr.",name:"Slawomir",middleName:null,surname:"Wilczynski",slug:"slawomir-wilczynski",fullName:"Slawomir Wilczynski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035U1loQAC/Profile_Picture_1630074514792",biography:"Professor Sławomir Wilczyński, Head of the Chair of Department of Basic Biomedical Sciences, Faculty of Pharmaceutical Sciences, Medical University of Silesia in Katowice, Poland. 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Editor-in-chief of the journal in the field of aesthetic medicine and dermatology - Aesthetica.",institutionString:null,institution:{name:"Medical University of Silesia",institutionURL:null,country:{name:"Poland"}}},editorTwo:null,editorThree:null,series:{id:"7",title:"Biomedical Engineering",doi:"10.5772/intechopen.71985",issn:"2631-5343"},editorialBoard:[{id:"5886",title:"Dr.",name:"Alexandros",middleName:"T.",surname:"Tzallas",slug:"alexandros-tzallas",fullName:"Alexandros Tzallas",profilePictureURL:"https://mts.intechopen.com/storage/users/5886/images/system/5886.png",institutionString:"University of Ioannina, Greece & Imperial College London",institution:{name:"University of Ioannina",institutionURL:null,country:{name:"Greece"}}},{id:"257388",title:"Distinguished Prof.",name:"Lulu",middleName:null,surname:"Wang",slug:"lulu-wang",fullName:"Lulu Wang",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRX6kQAG/Profile_Picture_1630329584194",institutionString:"Shenzhen Technology University",institution:{name:"Shenzhen Technology University",institutionURL:null,country:{name:"China"}}},{id:"225387",title:"Prof.",name:"Reda R.",middleName:"R.",surname:"Gharieb",slug:"reda-r.-gharieb",fullName:"Reda R. 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