\\n\\n
IntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\\n\\nIntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
\\n\\nLaunching 2021
\\n\\nArtificial Intelligence, ISSN 2633-1403
\\n\\nVeterinary Medicine and Science, ISSN 2632-0517
\\n\\nBiochemistry, ISSN 2632-0983
\\n\\nBiomedical Engineering, ISSN 2631-5343
\\n\\nInfectious Diseases, ISSN 2631-6188
\\n\\nPhysiology (Coming Soon)
\\n\\nDentistry (Coming Soon)
\\n\\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\\n\\nNote: Edited in October 2021
\\n"}]',published:!0,mainMedia:{caption:"",originalUrl:"/media/original/132"}},components:[{type:"htmlEditorComponent",content:'With the desire to make book publishing more relevant for the digital age and offer innovative Open Access publishing options, we are thrilled to announce the launch of our new publishing format: IntechOpen Book Series.
\n\nDesigned to cover fast-moving research fields in rapidly expanding areas, our Book Series feature a Topic structure allowing us to present the most relevant sub-disciplines. Book Series are headed by Series Editors, and a team of Topic Editors supported by international Editorial Board members. Topics are always open for submissions, with an Annual Volume published each calendar year.
\n\nAfter a robust peer-review process, accepted works are published quickly, thanks to Online First, ensuring research is made available to the scientific community without delay.
\n\nOur innovative Book Series format brings you:
\n\nIntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\n\nIntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
\n\nLaunching 2021
\n\nArtificial Intelligence, ISSN 2633-1403
\n\nVeterinary Medicine and Science, ISSN 2632-0517
\n\nBiochemistry, ISSN 2632-0983
\n\nBiomedical Engineering, ISSN 2631-5343
\n\nInfectious Diseases, ISSN 2631-6188
\n\nPhysiology (Coming Soon)
\n\nDentistry (Coming Soon)
\n\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\n\nNote: Edited in October 2021
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Increasingly complex environments together with the recent economic swings and substantially squeezed industrial margins put extra pressure on companies, and decision makers are pushed to increase operations efficiency and effectiveness. This book presents the contributions of a selected group of researchers, reporting new ideas, original results and practical experiences as well as systematizing some fundamental topics in Operations Management. Although it represents only a small sample of the research activity on Operations Management, people from diverse backgrounds, academia, industry and research as well as engineering students can take advantage of this volume.",isbn:null,printIsbn:"978-953-51-1013-2",pdfIsbn:"978-953-51-6318-3",doi:"10.5772/45775",price:119,priceEur:129,priceUsd:155,slug:"operations-management",numberOfPages:250,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"36030d013037e8d86323ddd323644874",bookSignature:"Massimiliano M. 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At “Tor Vergata” University in Rome lectures courses of Design of Manufacturing Systems and of Production Management at the School of Engineering; lectures Lean Manufacturing at the Master in Enterprise Engineering. Since May 2013, charged of the Quality of the Didactical and Research Activities of the Department of Enterprise Engineering. Instructor in several Master programs, including the MBA of Stoà Institute, the Lean Manufacturing Master of the University of Trieste, the iMBA of Argosy University (USA) and Università Marconi (Italy), the EMBA of Luiss “Guido Carli” University. Guest Professor at the Guizhou University of Finance & Economics in Guiyang, China. Founder and President of the Scientific Committee of Operations Management Team s.r.l., an Academic Spinoff operating in consultancy sector. Every year teaches more than 200 students in the Engineering School, and organizes an average of 15 students internships in various industrial companies. 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\r\n\r\n\tThis book aims to present advances and challenges of the design, manufacture and operation of wind turbines, and to provide a rich platform of research to the field of wind turbines. Suggested topics encompass wind measurement and forecasting, rotor blades, drive train technology, construction of tower and foundation, system integration and diagnostics, as well as offshore wind industry. The authors are encouraged to combine design, manufacturing processes and operation and maintenance procedures with a description of the implemented approaches and techniques, dealing with the individual subject as they find appropriate.
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He is also a consultant engineer at the Egyptian Organization for Standards and Quality and the rapporteur of the Technical Committee for Energy Systems Management. He was endorsed by Marquis Who's Who as a leader in the aerospace engineering industry.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"18593",title:"Prof.",name:"Karam",middleName:"Youssef",surname:"Maalawi",slug:"karam-maalawi",fullName:"Karam Maalawi",profilePictureURL:"https://mts.intechopen.com/storage/users/18593/images/system/18593.jpeg",biography:"Karam Y. Maalawi is a professor of Aeronautics and Mechanics at the Mechanical Engineering Department, National Research Centre in Cairo, Egypt. He holds a Bachelor of Science, Master of Science, and Doctor of Philosophy degrees in Aerospace Engineering (Cairo University). Dr. Maalawi has published extensively in the field of structural optimization and wind turbine design and performance. Likewise, he has utilized the vast range of knowledge at his disposal to contribute to several research projects regarding aerospace engineering technology, wind turbine structures and renewable energy applications. He is a consultant engineer at the Egyptian Organization for Standards and Quality and the rapporteur of the Technical Committee for Energy Systems Management. For his outstanding contributions to his profession, the National Research Centre has recognized him with two awards for engineering sciences. 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Since the middle of the nineteenth century, many natural products were obtained in a pure form from plants; most of these products are available to be used as active agents in modern medication. Despite the significant advances in synthetic drugs, side effects remain that necessitate the search for effective, inexpensive, and more accessible drugs. Medicinal plants may provide such valuable therapeutic alternatives. Use of traditional medicinal plants with analgesic effects has recently gained popularity worldwide because of their natural origin and fewer side effects [1]. Moreover, medicinal plant extracts and their fractions are used by 80% of the world population for their simple health care necessities. They are the significant source of natural drug molecules and secondary metabolites which can be used in modern medicine for the cure of various diseases. Throughout history, people relied on an old‐style traditional system of medicine to cure diseases and disorders, which with time has gained popularity and global significance. Present approximations suggest that in numerous developing countries, a large proportion of the population seriously trusts traditional specialists and local healers in addition to trusting medicinal plants and medicinal plants‐derived drugs to cure diseases, though modern drugs may be accessible in these countries. However, herbal medicines must be approved by local authorities before being prescribed.
Native people and early civilizations tested different plants and animal parts to determine what effect they have. Using trial and error methods, local healers and shamans found that particular plants or parts had therapeutic activity. These indicated the first crude drugs and this knowledge was passed down through the generations and arranged similar to the old‐style Chinese medicine as well as Ayurveda [2, 3]. Many traditional medicines have actual and useful effects, and extracts of these medicines have led to the discovery of bioactive molecules and to the growth of current chemically active pure drug discovery [3].
Recently, several people in developed countries have turned to complementary treatments including the use of therapeutic herbs [2]. In this context, the term Ayurvedic medicine has been introduced which is mainly in the form of a crude extract that consists of a mixture of several compounds; however, when the active agents are isolated and purified, they individually fail to give the desired activity. Therefore, pharmacological data on several medicinal plants and isolated compounds are required to regulate active compounds with the desired biological potency. Furthermore, modern methods of production, purification, and standardization should be followed to obtain plant‐derived materials of high quality [3]. In ancient times, humans extracted chemicals from plants for treatment of various diseases, and kept records of useful properties and uses of medical plants, such as willow bark and
Due to its frequent occurrence, pain is a public health problem with considerable socioeconomic effects. It is an indication of several illnesses and it is predicted that about 80–100% of the population will experience, for example, back pain once in life [4]. Pain treatment requires analgesics including, anti‐inflammatory medicines, which at maximum doses have analgesic properties. In this respect, inhibition of nitric oxide (NO) and prostaglandin E2 production has been reported as a potential therapy for different inflammatory disorders [5]. Though several anti‐inflammatory and analgesics drugs exist on the shelves, current drug therapy is related to certain adverse effects such as gastrointestinal irritation [6], bronchospasm, fluid retention, and extension of bleeding time. Consequently, it is necessary to discover new drugs with fewer adverse effects. Accordingly, people resort to medicinal plants for discovery and development of new drugs [7]. In addition, scientists discovered that extracts from medicinal plants can be a significant source of natural and safer new drugs for the treatment of inflammation and pain [8, 9].
Analgesics drugs include paracetamol (acetaminophenol), in addition to the nonsteroidal anti‐inflammatory drugs (NSAIDs) such as salicylates, and morphine and oxycodone isolated from opium. There are many classes of drugs available for treatment of pain. Each class has a dissimilar history of uses for treatment of different types of pain and in different types of people.
Analgesic selection is governed by the type of pain. For example, for neuropathic pain, traditional analgesics are less effective, whereas drugs that are not normally mentioned as analgesics, such as tricyclic antidepressants and anticonvulsants medicine, are more effective as pain killers [10]. In general, pain killers are not used if there have other serious side effects. For pain relief, drugs are classified based on either their chemical structures or on their uses for different classes of medical illnesses. Moreover, some drugs are arranged according to the requirements of people who use them. In other cases, these drugs are listed based on accessibility in a geographical zone, possibly to stop obtaining drugs which are prohibited there.
Acetaminophen (paracetamol) is a common medication to treat fever and pain [11]; this medicine is mostly used for slight and moderate body pain. On the other hand, paracetamol in combination with opioid are used for severe pain, such as pain after surgery [12]. Acetaminophen is used orally or taken intravenously [12] and its effect lasts between 2 and 4 hours. Acetaminophen is classified as slight analgesic [13] and is harmless at the recommended doses [13, 14].
Nonsteroidal anti‐inflammatory drugs (NSAIDs) are a class of medications that provide antipyretic and analgesic effects, and in higher doses have anti‐inflammatory potential. They are among the most commonly used analgesics for arthritic pain worldwide. The prominent members of this group of drugs are ibuprofen, aspirin, and naproxen, which are available and used in most countries [15]. Analgesic NSAIDs are nonnarcotic and are used as a nonaddictive alternate to narcotics.
The archetypal opioids (morphine) and all similar extracts, as well as other opioids, affect the cerebral opioid receptor coordination [16, 17]. Tramadol is a serotonin‐norepinephrine reuptake inhibitor (SNRI) through feeble μ‐opioid receptor agonist actions, whereas buprenorphine is a partial agonist of the μ‐opioid receptor [18]. Tramadol and venlafaxine are structurally very close to codeine that exerts analgesia not by individual opioid‐like properties but through less agonism of the μ‐opioid receptor and by acting as a serotonin‐releasing agent and a norepinephrine reuptake inhibitor [19–22]. Opioids, though very active analgesics, might have certain unfriendly side effects. Those patients starting morphine might experience vomiting and nausea [23].
Alcohol compounds are also documented to treat pain [24]; however, alcohols have biological, mental, and social properties that affect the significance of their use for treatment of pain [25]. Although reasonable usage of alcohol can reduce certain kinds of pain under certain conditions [26], the use of alcohol to cure pain, however, is encountered by the negative effects of extreme drinking [27].
Cannabis or medical marijuana is related to the use of cannabis and isolated cannabinoids to cure diseases and relieve pain [28]. In addition, cannabis and its compounds are used to treat chronic pain. The best‐known analgesic of these cannabinoids for treatment of pain is tetrahydrocannabinol, or the best known as THC [29–31].
In comparison, numerous mixtures of analgesic drugs have been determined to have insufficient effectiveness compared to similar doses of their separate mechanisms. Furthermore, these analgesic mixtures frequently result in consequences such as unintentional overdoses, often owing to misperceptions that arise from the many mentioned compounds and combinations [32]. Countless people use alternative medicine for pain relief. There are indications that some medications relieve some kind of pain more efficiently than others [33]; however, additional research would be essential to improve comprehension of the uses of many alternative medicine [34].
Numerous medicinal plants and their derived phytochemicals were evaluated for their analgesic and anti‐inflammatory effects. For example, extracts of bark as well as terpenoids obtained from
Natural products play a key role for living organisms. Primary metabolites are defined by Kossel as the main components of metabolic paths that are compulsory for life. Primary metabolites are related to important cellular roles, such as energy production, assimilation of nutrients, and development/growth. Secondary metabolites, in contrast to primary, are not essential and not required for the survival of living organisms [35–38].
Interestingly, secondary metabolites possess a broad range of functions. They comprise pheromones, which can act as community gesturing molecules with additional individuals of the same species [39–41]. Communication molecules entice and stimulate a symbiotic organism and agents to solubilize and transport various nutrients, including siderophores, as well as good arms such as venoms, repellants, and toxins, which are used as a prey and predators competitors [42]. It has been documented in the literature that nearly 10 million organic compounds have been discovered and many new and novel compounds are still being isolated and characterized in various parts of the world.
Regarding these compounds, one hypothesis is that they present a good benefit to the living organism which makes them. Another view says that these compounds have similarity to the immune system of living organisms, and although they have no function, yet they can afford assorted bioactive compounds which have important biological activity [42].
Naturally obtained agents such as aspirin, morphine, codeine, thebaine, and others have been reported to have analgesic activity. Aspirin derived from salicylic acid extracted from barks of the willow tree (
Chemical structures of analgesic compounds from medicinal plants.
Different types of active phytochemicals, such as steroids, alkaloids, tannins, phenol, and polyphenols are produced by medicinal plants [45–49]. In addition, a large number of plants that have been investigated are reported to have less pharmacologically active secondary metabolites identified. Plant‐derived molecules are mainly reported for their medical importance; this includes morphine, nicotine, quinine, steroidal, and many others [50]. A large number of presently recommended drugs have been derived from natural medicinal plants; some characteristic examples are given in next sections.
It has been reported in the literature that extracted natural products possess analgesic activity. The bark of willow trees has been recognized for pain‐relieving properties. It has been further reported that willow bark contains a bioactive compound, salicin, which hydrolyses into salicylic acid. As we know that derivative acetylsalicylic acid is known as aspirin and is used as a pain killer, the main mechanism of its action is inhibition of the cyclooxygenase enzyme (COX). There are two types of cyclooxygenase‐2 enzyme isozymes; COX‐1 (PTGS1) and COX‐2 (PTGS2). It is nonselective and permanently inhibits both form, but it is weakly more selective for COX‐1. COX produces prostaglandins most of them are pro‐inflammatory and thromboxanes, which promote clotting [51].
Nonsteroidal anti‐inflammatory drugs (NSAIDs) act via inhibition of cyclooxygenase enzyme (COX). Research findings suggest the opposing effects of nonsteroidal anti‐inflammatory drugs on COX. These drugs act by blocking the COX‐1 enzyme, which catalyzes the production of prostaglandins that are involved in numerous physiological functions, such as (a) maintenance of normal renal function in the kidneys, (b) mucosal protection in the gastrointestinal tract, and (c) proaggregatory thromboxane in the platelets. However, COX‐2 expression can be induced by cytokines and other inflammatory mediators in a number of tissues, including endothelial cells, and is believed to have a role in the mediation of pain, inflammation, and fever. COX‐2 agents only inhibit the COX‐2 enzyme, whereas traditional NSAIDs block both versions in general [16].
After extensive acceptance of the cyclooxygenase enzyme (COX‐2) inhibitors, it was revealed that many of the drugs in this class increase the risk of cardiovascular toxicity, which led to the removal of valdecoxib and rofecoxib, and others. On the other hand, etoricoxib appears comparatively safer to that of noncoxib NSAID diclofenac [17]. It is worth mentioning here that our research group has reported that pistagremic acid, a natural product isolated from
The key uses of NSAID medication are typically for joint‐ and spine‐related pain. Its mechanism of action is through interaction with pro‐inflammatory cytokines interleukin (IL‐1a, IL‐1b, IL‐6) and tumor necrosis factor (TNF‐α). Increased absorption of TNF‐α is thought to produce the cardinal symptoms of inflammation. These pro‐inflammatory cytokines result in chemo‐attractants for neutrophils and help them to stick to the endothelial from migration. They also stimulate white cell phagocytosis and the production of inflammatory lipid prostaglandin E2 (PGE2). The ability of NSAIDs to interfere with the production of prostaglandin during inflammatory cascade is the major mechanism cited for success of pain of medication. In normal pain, the archidonic pathway proceeds and results in the production of highly reactive mediators that are prostaglandin, prostacycline, histamines, and many others. These mediators cause the start of pain in the body.
An additional distinguished example is
Ziconotide, also known as SNX‐111, is a novel nonopioid analgesic drug. It is a synthetic version of ω‐conotoxin MVIIA (ω‐MVIIA), which is a peptide that is found in the venom of the fish‐eating marine snail,
Salvinorin A is the main active psychotropic molecule in
Pawhuskin A is a bioactive naturally occurring stilbene reported from
This chapter has focused on information and relevant literature pertaining to analgesic plants and their explored chemical constituents. Furthermore, unexplored medicinal plants reported to be used in folk medicine have been highlighted. This chapter also provides references to research carried out on analgesic drugs. Additionally, this chapter describes the main mechanisms of action of natural products poisoning presenting analgesic properties.
The authors are grateful to the Higher Education Commission of Pakistan and the University of Swabi, KPK, for financial support.
Biomedical signals are electrical activities recorded by sensors from a part of the body, such as the brain, heart, muscles, etc. They can be recorded as images e.g. functional Magnetic resonance Image (fMRI) from brain or a temporal signal e.g. Electrocardiogram (ECG), Electroencephalogram (EEG), Electromyogram (EMG), Galvanic Skin Response (GSR), etc. These signals contain useful information to analyse and understand the underlying physiological response of the body, thus they are also referred to as physiological signals. Biomedical signals are extensively used in healthcare to diagnose deceases and monitor health. With recent advancements and ease of using the devices to record the biomedical signals have open a window to use it to analyse and understand the day-to-day activities, emotions, and, experiences [1, 2, 3]. While recording the physiological activities through sensors, the signals are usually contaminated by noise and various artefacts [4]. Corrupted signals mislead the analysis and understanding of the underlying physiology [5]. The characteristics of wavelet to identify the time-localised events makes it suitable for the biomedical signals to clean, process, feature extraction, and analyse for various applications. Recent studies have shown the promising results of using wavelet in biomedical signals [6].
In this chapter, first, we introduce one kind of biomedical signal - EEG. We will explain the conventional features used in EEG studies. We will introduce the artefacts that commonly contaminate EEG signals, which makes it harder to use. The chapter then will move towards a short description of Wavelet analysis techniques, namely Continues Wavelet Transform (CWT), Discrete Wavelet Transform (DWT), and Wavelet Packet Decomposition (WPD). We would, then, compare CWT and STFT for EEG signal. Then, we will discuss artefact removal algorithms, with more details on Wavelet-based algorithms. The chapter will show the comparative analysis of artefact removal algorithm. The approach and analysis shown in this chapter for EEG signals can easily be applied to other biological signals.
The brain processes any information by means of neurons that use electrical and chemical signals to communicate by releasing and receiving neurotransmitters. The neural activity in the human brain is an electrical change. The brain generates electrical signals throughout the day for various activities. Studying these electrical signals is vital to understanding the neurophysiological behaviour of the brain [4]. A number of techniques are used to study brain activities. Functional magnetic resonance imaging (fMRI), Functional Near-Infrared Spectroscopy (firs), and Electroencephalography (EEG) recordings widely used techniques. The fMRI measures brain activity by scanning the blood flow. The fNIRS measures brain activity by measuring hemodynamic response in the brain through detecting the temporal changes in infrared light source. The EEG measures the electrical activity of the brain by electrodes placed on the scalp. Comparing to the other two, EEG measures brain activity directly, with high temporal resolution and most accessible and portable for the research. The fMRI has a high spatial resolution but very expensive, therefore it is mostly limited to medical diagnosis and treatments.
The EEG signal is measured by placing multiple electrodes on the scalp that measure the current flow from neurons. A setup for EEG recording is shown in Figure 1. Each neuron (brain cell), when activated, it produced an electrical and magnetic field around the scalp. Since there are 100 billion neurons in the brain, when an electrode is placed on the scalp, it measures the accumulative activity of many neurons together. The complex structure of the brain attenuates the electrical signals, therefore an electrode can record the brain activity, only when a large number of neurons generate enough potential. The EEG devices amplify the recorded signal to store and process it [4].
EEG recording setup: (a) a wireless device Emotiv Epoch mounted on a subject, transmitting EEG signal to a computer. (b) Electrode positions as 10–20 system, source:
The placement of electrodes has been standardised with the specific anatomical landmarks with a distance between electrodes as 10% or 20% of total length. This placement is called the 10–20 system, as shown in Figure 1b. The number of electrodes used for EEG recording varies, depending on the device. One of the low spatial resolutions can be of a 14-channel EEG device and high spatial resolution with 128 or 256 channels. The name of the electrode position is labelled as character followed by a number to identify the part of the brain. The characters are
The raw recording of EEG signal in the time-domain is complex to interpret. Similar to many other signals, frequency domain analysis has been widely used. The decades of work on EEG studies have identified five major frequency bands for EEG signals and established the correlation between behaviour and neural activity of a certain part of the brain. The frequency bands widely used are; Delta (
The signal channel raw EEG signal and corresponding frequency bands: Delta (
Due to multichannel signals, it is usually viewed as topographical brain activity (heatmap over an image of head) under different frequency bands. An example of 5 seconds EEG recording with a 14-channel device is shown in Figure 3. The first second of all the channels are used to compute the energy distribution over brain regions. In Figure 3, the top left shows the raw EEG signal and corresponding brain activity, which shows a high activity in the frontal lobe of the brain. However, under different frequency bands, the different part of the brain shows higher activity.
Topographical view of brain activity: Energy distribution of EEG recording over different brain regions under five frequency bands and raw signal.
The frequency bands; Delta, Theta, Alpha, Beta, and Gamma, are also called brain rhythms. Brain rhythms have been investigated over decades and a few characteristic behaviour of these brain rhythms have been established [4].
While recording, EEG signals are frequently contaminated with various artefacts. The most common types of artefacts are motion, muscular, ocular, and cardiac artefacts [4], which are shown in Figure 4. The motion artefacts are caused by the physical movement of the person’s body. As shown in Figure 4a, motion artefacts produce a sudden high valued spike in all the channels of EEG recording. The muscular artefacts, shown in Figure 4b are caused by any muscular contraction such as grinding the teeth. It produces high-frequency bursts in EEG recording as circled in the Figure 4b. The cardiac artefacts, shown in Figure 4c, are caused by the electrical activities of the heart. They appear as a weak form of QRS wave of heart and most likely to be appeared in the channels near to ears (temporal lobe), though it can be sometimes present in channels from the frontal lobe [7]. The ocular artefacts are slow oscillating waves appear on the frontal lobe, caused by the eye movements or closed eyes, as circled in the Figure 4d. The higher magnitude of the artefacts corrupts the EEG recording and leads to misinterpretations of the results and analysis [5]. Even though there are many algorithms to remove the artefacts, but there is always a possibility of losing the cerebral information while removing the artefacts.
Common type of artefacts in EEG. Corresponding artefacts are circled in the figure.
Most of the real-life signals are non-stationary in behaviour, which means their properties change over time. To localise the events of interest, time-frequency analysis is widely used. The conventional way of time-frequency analysis is the Short-Time Fourier Transform (STFT), where Fourier transform of the signal is taken over short-windows, resulting spectrogram plot. STFT has limitations on resolutions, due to Heisenberg’s uncertainty principle, e.g. improvement in time resolution results in poorer frequency resolution and vice-versa. The alternative to STFT is wavelet transform, which exploits the property of low-frequency signals being widespread over time and high-frequency bursts occurring on short intervals. Wavelet transform uses the variable size of windows with a wavelet function.
Wavelet analysis is usually applied in two ways, Continuous Wavelet Transform (CWT) and Discrete Wavelet Transform (DWT). CWT uses a wavelet function
4-level decomposition tree for (a) discrete wavelet transform (DWT), (b) wavelet packet decomposition (WPD).
As shown in Figure 5, block LP is a lowpass filter
As discussed, a conventional way to time-frequency analysis is STFT, however, using CWT with different wavelet functions can enrich the analysis with more details. In this section, we will show, how a continuous wavelet function (
A spectrogram is obtained using STFT, which is Fourier Transform computed for a short windows. STFT
CWT operation from Eq. (2) can be seen as convolution of input signal
where
Continues wavelet functions.
where
where
where
where
where
where
An example of using the above six wavelet functions for a small single-channel EEG segment is shown in Figure 7, along with spectrogram. It can be observed, spectrogram highlights a few events in signal (sharp peaks and lowpass wave), however, using CWT with different Wavelet functions, much richer information can be observed. Since, we observed that in the formulation of wavelet functions that they are similar to the underlying principle, we could also observe the similarities across different scalograms. Specifically, spectrogram using Complex Shannon and Complex Mexican hat wavelet are much similar. Interestingly, Morlate and Poisson wavelet functions are able to produce a better resolution towards lower frequencies.
Scalogram and spectrogram of a segment of signal channel EEG signal with six wavelet functions and STFT. Figure obtained using spkit python library -
Artefacts in EEG recording is a primary obstacle that all researchers have to deal with. There are decades of research work in literature to remove these artefacts [15, 16]. A range of methods have been proposed to remove the artefacts, starts with a statistical with interpolation method [17] and regression method [18]. The most commonly used approaches are based on Blind Source Separation (BSS) using Independent Component Analysis (ICA) [19, 20]. ICA based approach have been widely explored with statistical measures [21, 22, 23, 24], and variant of ICA as FastICA, InfoMax, and Extended InfoMax [25, 26, 27]. Wavelet-based approaches are well suited for time-localised short events, as opposed to ICA. This property has been exploited to remove artefacts from single-channel EEG. In contrast to a single channel, wavelet has also been used for multi-channel EEG [28] and in combination with ICA [29, 30, 31, 32, 33, 34], in which identified artifactual component is cleaned with wavelet rather than removed. The ICA-based approaches can only be applied to multi-channel EEG and need an expert to select artifactual component, which has been automated with heuristics [21, 35, 36]. In contrast, most wavelet-based algorithms remove artefacts from each channel individually.
The key idea of wavelet-based artefact removal algorithms is to apply DWT on single-channel EEG signal
where
A block diagram of ATAR algorithm [
where
Wavelet filtering modes for ATAR algorithm. For
where
Figure 10 shows a visual comparative analysis of wavelet-based approaches (i.e. Global threshold, STD threshold, and ATAR algorithm) and ICA based approaches (FastICA, InfoMax, and Extended-InfoMax) to remove the artefacts. It is visually apparent that wavelet-based approaches are better than ICA-based approaches. Among wavelet-based approaches, using ATAR gives much control over Global and STD based threshold selection. Other quantitative analyses of the above-mentioned approaches are discussed in the article [41], which also demonstrate the effect of tuning parameter and filtering modes on different predictive tasks of EEG signal. The formulation of relationship, algorithmic implementation details, and comparative results are given in article [41].
Comparison of artefact removal approaches from [
This chapter presents the overview of Wavelet for EEG analysis. The first chapter introduces EEG signal, commonly used features for predictive analysis, and artefacts that often contaminate EEG signal. Then chapter discusses the Wavelet analysis approaches, namely CWT, DWT, and WPD. The richness of CWT over STFT for time-frequency analysis using various wavelet functions is demonstrated. Finally, the artefact removal algorithms based on wavelet and ICA are discussed. The comparative analysis present in the chapter shows that the wavelet-based approach outperforms ICA based approach. Specifically, a recent algorithm (ATAR) allows controlling the removal or suppression of assumed artifactual components in the signal, which can be tuned to improve the performance of any predictive tasks. The techniques presented in this chapter show how wavelet can be used for EEG studies to extract rich information and removing the artefacts. The comparative analysis shows wavelet based approaches are well suited for EEG signal processing. Further, similar approaches can be used with other biomedical signals such as electrocardiogram (ECG or EKG), Electromyography (EMG) etc.
"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges".
\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.
",metaTitle:"About Open Access",metaDescription:"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges.\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.",metaKeywords:null,canonicalURL:"about-open-access",contentRaw:'[{"type":"htmlEditorComponent","content":"The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\\n\\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\\n\\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
\\n\\n“By “open access” to [peer-reviewed research literature], we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited” (reference: http://www.budapestopenaccessinitiative.org)
\\n\\nOAI-PMH
\\n\\nAs a firm believer in the wider dissemination of knowledge, IntechOpen supports the Open Access Initiative Protocol for Metadata Harvesting (OAI-PMH Version 2.0). Read more
\\n\\nLicense
\\n\\nBook chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen upholds a very flexible Copyright Policy. There is no copyright transfer to the publisher and Authors retain exclusive copyright to their work. All Monographs/Compacts are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Read more
\\n\\nPeer Review Policies
\\n\\nAll scientific works are Peer Reviewed prior to publishing. Read more
\\n\\nOA Publishing Fees
\\n\\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
\\n\\nDigital Archiving Policy
\\n\\nIntechOpen is committed to ensuring the long-term preservation and the availability of all scholarly research we publish. We employ a variety of means to enable us to deliver on our commitments to the scientific community. Apart from preservation by the Croatian National Library (for publications prior to April 18, 2018) and the British Library (for publications after April 18, 2018), our entire catalogue is preserved in the CLOCKSS archive.
\\n\\nOpen Science is transparent and accessible knowledge that is shared and developed through collaborative networks.
\\n\\nOpen Science is about increased rigour, accountability, and reproducibility for research. It is based on the principles of inclusion, fairness, equity, and sharing, and ultimately seeks to change the way research is done, who is involved and how it is valued. It aims to make research more open to participation, review/refutation, improvement and (re)use for the world to benefit.
\\n\\nOpen Science refers to doing traditional science with more transparency involved at various stages, for example by openly sharing code and data. It implies a growing set of practices - within different disciplines - aiming at:
\\n\\nWe aim at improving the quality and availability of scholarly communication by promoting and practicing:
\\n\\n\\n"}]'},components:[{type:"htmlEditorComponent",content:'
The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\n\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\n\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
\n\n“By “open access” to [peer-reviewed research literature], we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited” (reference: http://www.budapestopenaccessinitiative.org)
\n\nOAI-PMH
\n\nAs a firm believer in the wider dissemination of knowledge, IntechOpen supports the Open Access Initiative Protocol for Metadata Harvesting (OAI-PMH Version 2.0). Read more
\n\nLicense
\n\nBook chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen upholds a very flexible Copyright Policy. There is no copyright transfer to the publisher and Authors retain exclusive copyright to their work. All Monographs/Compacts are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Read more
\n\nPeer Review Policies
\n\nAll scientific works are Peer Reviewed prior to publishing. Read more
\n\nOA Publishing Fees
\n\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
\n\nDigital Archiving Policy
\n\nIntechOpen is committed to ensuring the long-term preservation and the availability of all scholarly research we publish. We employ a variety of means to enable us to deliver on our commitments to the scientific community. Apart from preservation by the Croatian National Library (for publications prior to April 18, 2018) and the British Library (for publications after April 18, 2018), our entire catalogue is preserved in the CLOCKSS archive.
\n\nOpen Science is transparent and accessible knowledge that is shared and developed through collaborative networks.
\n\nOpen Science is about increased rigour, accountability, and reproducibility for research. It is based on the principles of inclusion, fairness, equity, and sharing, and ultimately seeks to change the way research is done, who is involved and how it is valued. It aims to make research more open to participation, review/refutation, improvement and (re)use for the world to benefit.
\n\nOpen Science refers to doing traditional science with more transparency involved at various stages, for example by openly sharing code and data. It implies a growing set of practices - within different disciplines - aiming at:
\n\nWe aim at improving the quality and availability of scholarly communication by promoting and practicing:
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. 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Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. 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Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. He has contributed in stochastic estimation of control area especially, in the Multiple Target Tracking and Interactive Multiple Model (IMM) research, Ball & Beam Control Problem, Robotics, Levitation Control. He has contributed in developing Algorithms for Fingerprint Matching, Computer Vision and Face Recognition. He has been supervising Pattern Recognition, Formal Languages and Distributed Processing projects for several years. He has reviewed many books on Management, Computer Science. Currently, he is an active and permanent reviewer for many international conferences and symposia and the program committee member for many international conferences.\nIn teaching he has taught the core computer science subjects like, Digital Design, Real Time Embedded System Programming, Operating Systems, Software Engineering, Data Structures, Databases, Compiler Construction. 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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:"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:5907,totalCrossrefCites:19,totalDimensionsCites:32,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. 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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:"41589",doi:"10.5772/50323",title:"The Role of the Amygdala in Anxiety Disorders",slug:"the-role-of-the-amygdala-in-anxiety-disorders",totalDownloads:9707,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:7183,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:1455,totalCrossrefCites:13,totalDimensionsCites:24,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:192987,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:4596,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:3523,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:3609,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:1349,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:"82319",title:"Traumatic Optic Neuropathy",slug:"traumatic-optic-neuropathy",totalDownloads:2,totalDimensionsCites:0,doi:"10.5772/intechopen.104731",abstract:"Traumatic optic neuropathy (TON) is a specific neurological sequence of traumatic brain injury (TBI). It has a different mechanism than other most neurologic complications of head trauma and its consequences can be devastating. The damage can be from direct penetrating trauma or bone fracture injuring the optic nerve directly or secondary to indirect blunt trauma (usually causing traction). The diagnosis of TON is based on the clinical history and examination findings indicative of optic neuropathy, especially the presence of defective pupillary light response. TON can cause only mild vision loss but, in some cases, severe vision loss is present. Imaging findings can support the diagnosis, and provide information on the mechanism as well as treatment options. The treatment options include observation alone, systemic steroids, erythropoietin, surgical decompression of the optic canal, or combination. The evidence base for these various treatment options is controversial and each treatment has its side effects and risks. Poor prognostic factors include poor visual acuity at presentation, loss of consciousness, no improvement in vision in the first 48 hours, and evidence of optic canal fractures on neuroimaging.",book:{id:"11367",title:"Traumatic Brain Injury",coverURL:"https://cdn.intechopen.com/books/images_new/11367.jpg"},signatures:"Ainat Klein and Wahbi Wahbi"},{id:"82203",title:"Resting-State Brain Network Analysis Methods and Applications",slug:"resting-state-brain-network-analysis-methods-and-applications",totalDownloads:19,totalDimensionsCites:0,doi:"10.5772/intechopen.104827",abstract:"Resting-state fMRI has been widely applied in clinical research. Brain networks constructed by functional connectivity can reveal alterations related to disease and treatment. One of the major concerns of brain network application under clinical situations is how to analyze groups of data to find the potential biomarkers that can aid in diagnosis. In this paper, we briefly review common methods to construct brain networks from resting-state fMRI data, including different ways of the node definition and edge calculation. We focus on using a brain atlas to define nodes and estimate edges by static and dynamic functional connectivity. The directed connectivity method is also mentioned. We then discuss the challenges and pitfalls when analyzing groups of brain networks, including functional connectivity alterations, graph theory attributes analysis, and network-based statistics. Finally, we review the clinical application of resting-state fMRI in neurorehabilitation of spinal cord injury patients and stroke patients, the research on the mechanism and early diagnosis of neurodegenerative diseases, such as multiple system atrophy, as well as the research on brain functional network alteration of glioma patients.",book:{id:"11742",title:"Neurophysiology",coverURL:"https://cdn.intechopen.com/books/images_new/11742.jpg"},signatures:"Yunxiang Ge and Weibei Dou"},{id:"82099",title:"Recent Advances in the Development of Biofluid-Based Prognostic Biomarkers of Diffuse Axonal Injury",slug:"recent-advances-in-the-development-of-biofluid-based-prognostic-biomarkers-of-diffuse-axonal-injury",totalDownloads:13,totalDimensionsCites:0,doi:"10.5772/intechopen.104933",abstract:"Even though head injury is a silent pandemic of the century producing immense social and economic impact, predictive models have not been established to develop strategies promoting the development of reliable diagnostic tools and effective therapeutics capable of improving the prognosis. Diffuse axonal injury (DAI) is a type of traumatic brain injury (TBI) that results from a blunt injury to the brain. Discovering biomarkers for DAI have been a matter of debate and research. A number of studies have reported biomarkers that are correlated with severity of TBI but no conclusive and reproducible clinical evidence regarding the same has been put forward till now. Additionally, many DAI biomarkers have limitations so that they cannot be generalized for universal applications. The properties of these biomarkers should be extensively researched along with the development of novel biomarkers to aid important clinical decisions for the benefit of the society. This chapter summarizes the existing biofluid-based biomarkers, critically examines their limitations and highlights the possibilities of a few novel biomolecules as prognostic biomarkers of DAI.",book:{id:"11367",title:"Traumatic Brain Injury",coverURL:"https://cdn.intechopen.com/books/images_new/11367.jpg"},signatures:"Vinu V. Gopal, Rinku Raj Mullasseril and Goutam Chandra"},{id:"81998",title:"Understanding the Neuropathophysiology of Psychiatry Disorder Using Transcranial Magnetic Stimulation",slug:"understanding-the-neuropathophysiology-of-psychiatry-disorder-using-transcranial-magnetic-stimulatio",totalDownloads:5,totalDimensionsCites:0,doi:"10.5772/intechopen.103748",abstract:"Transcranial magnetic stimulation (TMS) is a safe and non-invasive tool that allows researchers to probe and modulate intracortical circuits. The most important aspect of TMS is its ability to directly stimulate the cortical neurons, generating action potentials, without much effect on intervening tissue. This property can be leveraged to provide insight into the pathophysiology of various neuropsychiatric disorders. Using multiple patterns of stimulations (single, paired, or repetitive), different neurophysiological parameters can be elicited. Various TMS protocol helps in understanding the neurobiological basis of disorder and specific behaviors by allowing direct probing of the cortical areas and their interconnected networks. While single-pulse TMS can provide insight into the excitability and integrity of the corticospinal tract, paired-pulse TMS (ppTMS) can provide further insight into cortico-cortical connections and repetitive TMS (rTMS) into cortical mapping and modulating plasticity.",book:{id:"11742",title:"Neurophysiology",coverURL:"https://cdn.intechopen.com/books/images_new/11742.jpg"},signatures:"Jitender Jakhar, Manish Sarkar and Nand Kumar"},{id:"81646",title:"Cortical Plasticity under Ketamine: From Synapse to Map",slug:"cortical-plasticity-under-ketamine-from-synapse-to-map",totalDownloads:17,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:30,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"}],onlineFirstChaptersTotal:13},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:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:318,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:106,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:19,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:15,numberOfOpenTopics:5,numberOfUpcomingTopics:0,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:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"June 11th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,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},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. 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He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. 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