\r\n\tOver the years, the concept of maintenance became more comprehensive, reducing fault occurrence and increasing industrial system availability. Besides, reliability, safety, and criticality requirements were associated with the system or equipment under analysis. Maintenance strategies or schemes can be classified as corrective (run-to-break), preventive (time-based), and predictive (condition-based maintenance). Corrective maintenance is only performed after an occurrence of a fault. Therefore, it involves unexpected breakdowns, high costs, changes in the production chain, and it could lead to catastrophic events. Preventive maintenance and interventions occur based on a scheduled maintenance plan or the equipment's mean time between failures. Although it is more effective than corrective maintenance, unexpected failure may still occur by preventing most failures. Additionally, the process cost is still high, especially the costs associated with labor, inventory, and unnecessary replacement of equipment or components.
\r\n\tOn the other hand, predictive maintenance analyses the equipment condition so that a possible fault can still be identified at an early stage. Predictive maintenance aims to identify a machine anomaly so that it does not result in a fault. Such maintenance involves advanced monitoring, processing, and signal analysis techniques, which are generally performed non-invasively and, in many cases, in real-time. In the case of machines or processes, these techniques can be developed based on vibration, temperature, acoustic emission, or electrical current signal monitoring. It should be noted that monitoring such signals or parameters to verify the operating condition is called condition monitoring. Condition monitoring aims to observe the machine's current operational condition and predict its future condition, keeping it under a systematic analysis during its remaining life. In this sense, a fault condition can be detected and identified from systematic machine condition monitoring. A diagnosis procedure can be established, whereby properly investigating the fault symptoms and prognosis.
\r\n\t
\r\n\tThis book will aim to merge all these ideas in a single volume, aggregate new maintenance experiences, apply new techniques and approaches, and report field experiences to establish new maintenance processes and management paradigms.
\r\n\t
Developing technology, rehabilitation services, and change in health definitions have brought about the use of different treatment methods as well as traditional treatments. Some of these methods are virtual reality, animal-assisted practices, and aqua therapy. Animal-assisted approaches are defined as using human and animal interaction in therapeutic methods to eliminate or decrease the problems that an individual experiences in the physical, psychological, and social environments. These methods consist of two basic topics, namely animal-assisted activities (AAA) and animal-assisted therapies (AAT). Both AAA and AAT can be implemented in an interdisciplinary team approach. Occupational therapists (OTs), physiotherapists, speech therapists, special education specialists, and psychologists are core elements of these approaches. In recent years, these methods have also been used to increase social interaction with physical structure and functions in neurodevelopmental disorders such as autism spectrum disorder and cerebral palsy in addition to mental health disorders such as depression and anxiety to increase the independence in daily life activities and social participation.
\nThe American Veterinary Medical Association has been involved in human and animal interaction as psychological and physical functions between human beings and animals. In this interaction, they define individual’s quality of life as a structure that contributes positively to their improvement [1]. Animal-assisted rehabilitation, the inclusion of animals that can interact with humans such as cats, dogs, and horses, has an active role in the rehabilitation process with the aim of achieving rehabilitation goals [2, 3]. When such approaches are incorporated into rehabilitation programs, the general condition of the individual and the treatment principle that the rehabilitation team has followed are taken into account [4, 5]. Animal-assisted rehabilitation approaches, rather than a stand-alone approach, are a strategic concept where multiple professionals work together to achieve interdisciplinary goals within a single goal [5]. This framework consists of three basic questions. The first question is “what are the benefits of the individual animal and therapeutic activities including animals?” The second question is “how to include the animal to the rehabilitation process?” The third question is “what are the most appropriate activities for the individual?” [1] Based on the answers of these questions, animal-supported approaches are grouped under two main headings: animal-assisted activities (AAA) and animal-assisted therapies (AAT). When therapeutic properties of AAA are investigated, it has been found that it helps to reduce the level of stress and anxiety and indirectly increasing the self-confidence and socializing. It is stated that AATs were predominantly used to support neurodevelopmental substructures of individuals and make a positive contribution to their well-being [6].
\nAnimals play an important role in the history of the disease with different ideas about disease and its treatments. However, the precise characteristics of these roles depend not only on the prevailing views of animals but also on supernatural or “scientific” belief systems in which they are buried. Probably, the oldest of these belief systems, often called “animism,” includes the concept that all natural beings, as well as other natural objects and phenomena, are circulated by an invisible soul, spirit, or “essence,” but with conscious bodybuilding, the carrier can act independently of the body when it dreams or is unconscious. In a typical animist worldview, all statements of illness or misfortune are the direct result of attacks by the other angry or evil spirits encountered during these periods of unconsciousness toward the spirit of the person or the “truth.” In some cases, these spiritual attacks are thought to be reprisals. It is the result of moral accusation that the person intentionally or mistakenly does. On the other hand, a person can be the innocent victim of a malicious shaman or the attack of souls acting in the name of witches. Tips about the root of spiritual attacks are provided by the contents of dreams or images just before certain illnesses, injuries, or misfortunes [7, 8, 9]. Animist belief systems carry the characteristics of all communities that engage in hunting, and disturbing animal spirits among these communities are often seen as the most common source of malicious mental influences. Many hunters believe that the souls of hunted animals in the tribe have the ability to seek revenge as the ghosts of killed people. To avoid this accretion, all animals, whether dead or alive, are treated with great respect [10]. In other hunting and feeding cultures, there were more specific moral associations between people and the animals they hunted for food. For example, many Native American and Eurasian peoples believe in the concept of personal “protective spirits” [7, 11]. Between Ojibwa (Chippewa) and the Algonian neighbors, these spirits were known as
The end of the seventeenth century which was called “Age of Enlightenment” brought some changes in the public perception of animals that are well documented by historians of the modern age [13, 14]. Among these changes, contrary to the pre-medieval and renaissance periods, sympathetic thoughts began to dominate attitudes toward animals and nature [15]. While perceptions of wildlife and threats to wildlife have diminished from prevalence, pet-feeding habits have expanded to aristocratic and middle-class communities living in newly founded cities. This change in animal-related attitudes and behaviors could at least partly reflect Europeans’ migration from rural areas to the towns and cities, and the rapid spread of the human population. This rural migration made it possible for the population to be adapted to systems designed for growth [8, 14]. The reformers of the eighteenth century, deriving their authority from the works of John Calvin and Thomas Hobbes, thought that they could indirectly learns from the innate, unfavorable characteristics of children by using children’s behavior to take care and control real animals [16]. Compassion and anxiety for the health of animals became one of the didactic themes of children’s literature that lived in the eighteenth and nineteenth centuries; the main aim was to inspire the morality of the good and sex, respectively, especially in boys [17, 18, 19]. In the late eighteenth century, theories about the social effects on animal care were initiated in the treatment of mental illnesses. The best-documented studies took place in The York Retreat in England. The York Retreat used more innovative methods than the mental treatment methods used at that time. In this study, prisoners were encouraged to do handwriting, writing and reading books, and they were also allowed walking freely around the courtyards and gardens of the Retreat, where small pets were also part of the Retreat and prisoners could interact with them. In his description of the Retreat (1813, p. 96), Samuel Tuke, the founder’s grandson, described how the internal courtyards of the Retreat were supplied “with a number of animals; such as rabbits, sea-gulls, hawks, and poultry. These creatures are generally very familiar with the patients: and it is believed they are not only the means of innocent pleasure; but that the interaction with the sometimes tends to awaken the social and benevolent feelings.” In the nineteenth century, pets became an increasingly popular feature in the psychiatric departments of hospitals in the UK. For example, in a highly critical report on terrible conditions for patients in Bethlem Hospital in the 1830s, British Charity Commissioners proposed that the shelter of people with a mental problem is provided support for treatment of sheep, rabbits, apes or other domestic pets, they have also been described as social animals. Such recommendations are clearly taken seriously. According to a paper published in Illustrated London News of 1860, the regulations at Bethlem Hospital have been redesigned according to the stimulus [20]. It has been observed that animal companions have beneficial and therapeutic effects in the treatment of physical disorders. Florence Nightingale, for example, observed and wrote in Notes on Nursing (1880) that “a small pet is a particularly good friend, especially for the patient, long chronic cases” [21].
\nDespite the success of animal-supported institutional care in scientific studies during the nineteenth century, with the development of evidence-based medicine in the early twentieth century, the use of animals in hospitals has declined dramatically [20]. For the next 50 years, animals were used in the context of zootomic illnesses, public health concerns, or psychoanalytic theories of the origin of mental illnesses. Sigmund Freud’s ideas concerning the origins of neurosis tended to reiterate the Hobbesian idea of mankind’s inherently beast-like nature [16]. According to Freud, infants and young children are in fact similar to animals, as long as they are governed by instinctual desires or could be influenced by organized basic biological functions such as nutrition, defecation, sexuality, and self-protection. Freud describes this basic and animal-like instinct of human nature as “identity.” As children mature, their parents’ behaviors will either cause too much impulsive behavior by reacting to the child’s inner aggression or induce their sense of fear, guilt, and socialization. The suppression of these children under the consciousness of children ensures that their behavior in their daily lives is healthy. But they are like animals in their 30s. Freud refers to this as a bottled animal chart. It results in explosive situations where the individual cannot go out on regular outings [22]. Freud interpreted the recurrent animal images of his patients’ dreams and “freethinking” as metaphorical means that hid the unacceptable thoughts and feelings of humans. “The Wild Beast” he argued, “It makes him happy that other dreams come true while the passionate spirits of the dreamer are afraid of himself” [23]. These crude thoughts and impulsions threaten the “ego” so deeply that they can be ignored in the dark corners of the consciousness in proportion to the capacity of the subconscious within the hours when at least one person is awake. According to Freud and his followers, the aim of psychoanalysis is to reveal these scary residents of the subconscious, to reveal them as they are in their true nature, and thus to neutralize them [24]. The notion of “id,” Freud defines as the basic “animal” essence of human nature, contains more than a superficial resemblance to animistic and shamanic ideas about animal spirits and protective spirits, including bad thoughts/“evil self” or spiritual origins [24]. In the study on Carl Jung, especially his discussions of mythological archetypes in dreams and visions, and his concept of the “Collective Unconscious,” this resemblance becomes more or less explicit [25]. It is also echoed in the writings of Boris Levinson, the founder of “pet-facilitated therapy.” In his book
According to Levinson, the solution to this growing sense of alienation is through positive relationships with the animals, as if dogs, pets, and other domestic animals are within themselves. It is emphasized that this relationship has increased the quality of life by positively contributing to the solution of the problems experienced by the individual in the spiritual sense [27]. Levinson went one step further to the idea that Freud propagated and suggested symbolic patterning system of things where we fear to confront animals; in order to argue that their relationship with animals is an important part of human evolution and that it is now an integral part of our present psychological well-being [26].
\nThere has been considerable development in the theoretical substructure of animal-assisted approaches during the last 20 years and, at least in part, in response to the skepticism shown toward blood-based medicine. This substructure offers the basis for demonstration as a psycho-mental mediator by providing relief from relatively metaphysical-based thoughts about animals [24]. The primary catalyst for this change of emphasis was a single, groundbreaking study of 92 outpatients from a cardiac care unit who, statistically speaking, were found to live longer if they were pet owners [28]. This finding prompted a whole series of other health-related studies as well as stimulating a lot of discussion concerning the possible mechanism(s) responsible for the apparent salutary effects of pet ownership. Of these, at least two have stood the test of time. According to the first, animals are able to induce an immediate, physiologically de-arousing state of relaxation simply by attracting and holding our attention. According to the second, companion animals are capable of providing people with a form of stress-reducing or stress-buffering social support [29, 30]. Although the de-arousing effects of animal contact have been demonstrated by a considerable number of recent studies, little evidence exists at present that these effects are responsible for more than transient or short-term improvements in physiological parameters, such as heart rate and blood pressure. On the other hand, pets serving as a source of social support seem to provide a relatively high level of evidence for the longer-term benefits of animal companionship [31].Cobb has defined social support as “relationships that direct, to emphasize and give importance to, to describe that it is the pattern of mutual obligations.” However, the newer authors have expressed it as “perceived social support” and “social networking” characteristics. The first represents a qualitative definition of the degree of satisfaction from the support that one receives from certain social relations; the second is a more quantitative measure involving the number, frequency, and propensity of the person’s general social interactions [32]. However, the importance of social support to human well-being, which we wanted to describe, has been regarded as one of the top-down issues throughout history. Loneliness—lack of social support—has always been seen as a painful and distasteful phenomenon; since ancient times, societies have used single-cell imprisonment, exile, and social mobilization as methods of punishment. This, in fact, shows that loneliness is actually the basic punishment method. In addition, religious themes explain in detail the psychological effects of autobiographical, social isolation that homeland traitors and prisoners of war wrote. Many of them describe physical torture in a way that will emotionally, often sharply, up to the apex of gradual descent. This decrease in pain is associated with the onset of a serious indifference and hopelessness, which usually requires catatonic deprivation [29]. In the last 10–15 years, a comprehensive medical literature has emerged confirming that there is a strong and positive link between social support and improved human health and survival [33, 34, 35]. There is a great deal of social support in reducing the adverse effects of stress, which chronic life has brought. With the controversy still underestimating these effects, many authorities now accept the judgment that the main benefits arise from the buffering or healing capacities of long-term effects of supporting social relations [36]. Theoretically, this beneficial effect of social support should be applied to any positive social association. It has been observed that positive behaviors are exhibited within the two parties in relation to which one is loved or respected. Despite the increasing evidence for anthro-zoological research in the recent past, the idea that animal attendants contribute socially to human health, however, received very limited medical attention [8].
\nAAT is used as a therapeutic approach in rehabilitation. AAT approaches are being used all over the world in order to improve not only the emotional and psychosocial states but also the physical, sensory, and cognitive skills positively for individuals with various diseases or of different ages [37, 38]. Rehabilitation practices include holistic approaches, with divergence toward children, adolescents, adults, and elderly people.
\nIt is known that there are many neurological, physiological, and genetic diseases seen in children, and the rehabilitation practices are widely used in these children [39]. In literature, AAT is commonly used in children with cerebral palsy, developmental neurological disorders, autism spectrum disorders, sensory processing disorders, degenerative neurological and muscle disorders that mainly focus on control of muscle tonus, mobility, and balance [40]. When the elderly and adult population rehabilitation applications are examined, it is seen that animal-assisted approaches are preferred in the treatment of diseases such as multiple sclerosis, head trauma, post-traumatic neurological conditions, Alzheimer Disease, dementia, anxiety, and depression [41, 42, 43]. These diseases can cause a reduction in postural symmetry and control, and deterioration in cognitive skills like attention, memory, and executive functions [37].
\nAll of these patients with diseases, whether young or old, were psychologically affected, and their motivation decreased during rehabilitation. It is known that sensory, emotional, and physical characteristics of animals can be utilized to increase the level of motivation in rehabilitation. In fact, in most developed countries today, health-care providers employ animal-assisted therapy in a wide range of settings, including rehabilitation centers, acute care, psychiatric centers, and outpatient clinics. For example, doctors’ consulting rooms have fish tanks in their waiting rooms to promote a sense of calm [44]. It is now well known that the presence of animals can induce relaxation, increase positive emotions, reduce resistance to treatment, and put patients’ minds at ease.
\nAwareness of the advantages and disadvantages of the animals and species used by the professional practitioner team in rehabilitation practices involving many health disciplines involved in this area positively affect the effectiveness of rehabilitation [6]. At the same time, it also emphasizes the importance of knowing the animal’s unique structure and instincts in these studies [6, 37]. Most studies and programs in AAT utilize animals such as livestocks, dolphins, dogs, cats, birds, hamsters, or horses [45]. All animals have certain advantages and disadvantages within themselves, so that the practitioner can make arrangements according to the individual and individual’s needs.
\nIt is mentioned in the literature that all farm animals can be easily included in treatment approaches as long as they are checked by the veterinarian for good health and reliability. The benefits and difficulties of incorporating livestock into therapy approaches may vary according to the therapist’s rehabilitation goal. These animals are preferred by the occupational therapists (OTs) in rehabilitation applications, in particular for those individuals who have difficulty in independent daily living skills, in terms of a large living space, and special need for care. There are also studies showing that AAT with livestock affects individuals’ motor and cognitive functions positively [46, 47]. They are preferred by OTs because they can help improve their equilibrium, hand-eye coordination, executive function, and hand skills of individual.
\nAAT in individuals with both physical and cognitive impairment is a useful method for facilitating human interaction, stress reduction, relieving depression, and increasing motor and cognitive functions in therapeutic purposes. The dolphin is one of the most important animal species that provide them. There are two main reasons for choosing the dolphin in therapy session when compared to other species: the first is the dolphin’s intelligence and learning style and the second is water as stress reduction [45]. On the other hand, there are also some difficulties or disadvantages to working with dolphins. Researchers suggest that the dolphin has some risks due to the fact that it is not a domestic animal, the results of evidence-based studies are very low, and treatment conditions come with very high costs [48].
\nDolphin-assisted therapy is commonly used in people with head injuries, schizophrenia, cancer, or other chronic diseases for improving both gross and fine motor skills, developing sensory integration, and increasing communication skills. Nathanson et al. indicated that measurable improvement was observed in the functioning in children with autism spectrum disabilities when dolphin therapy was conducted 5 days per week for at least two weeks [49]. It is suggested that the dolphin should be used as a supportive therapy in the healing and motivational aspects as well as the positive aspects in human beings.
\nOne of the animals frequently used in therapy by professionals working in various fields is the dog to improve the physical, cognitive, functional, and social skills of individuals. The most important areas of use are autism spectrum disabilities in children and visually impaired individuals [50]. Many studies mentioned that the degree of independence in daily living activities improved when using dogs as a therapy companion [50, 51]. It is observed that dogs, one of the most important parts of AAT, interact better with people than other animals [6]. Dogs are highly preferred by experts because they are both AAA and AAT suitable for use in therapeutic approaches.
\nDogs are often preferred for both children and adults in therapy because they are friendly, sympathetic, obedient, and playful. They are also used as a guide for the blind, as walking aids for physically challenged, and a hearing assistance for the deaf. Many studies have shown that dogs offer vital benefits in terms of reducing functional disability and facilitation of communication and interaction in humans [38, 52]. Therefore, it is important to remember that dogs can be used for animal-assisted approaches toward therapy, primarily for all ages and patients with diagnosis.
\nCats can often help in both AAA and AAT like the dogs [53]. They are free spirited and can interact with humans and provide sensory and emotional support to individuals. Due to these characteristics, cats have shown that they especially affect individuals’ well-being and quality of life positively [6]. It is known that they can be easily used in supplied everywhere as well as in the living space of the individual. However, it can be said that the most common disadvantage of using cats in therapy is their allergic furs [54]. It is therefore necessary that the therapist who applies the animal-assisted approach to patients has to understanding and know the patient’s allergic conditions and chronic diseases.
\nInterest in AAT is increasing day by day in the literature. While it is generally believed that cats are widely used in AAT, we found no qualified studies that used a cat [37]. So, there is a need for OTs to investigate the disadvantages of utilizing a cat in the therapeutic approaches on patients with having a disability in daily life skills.
\nPets that are described as small pocket animals, feathers and furs of varying lengths, color, and characteristics that vary in appearance are categorized in this section. Small animals consist of fish, birds, hamsters, turtles, and rabbits, which can be found easily in the classrooms, offices, or schools rather than other large animals. OTs can benefit from the use of these animals in the development of activities in areas requiring community participation.
\nThese animals often carry on with their lives as an ordinary part of the circle. But at this time, it is especially used in therapeutic approaches for both children and psychiatric patients in terms of learning to take responsibility for animals [43, 55]. These animals have a disadvantage in terms of the limited span of life (2–5 years) which can hamper rehabilitation process [56]. Although these animals are preferred in performing small tasks in AAA, the number of studies in the literature is inadequate.
\nAmong animal-assisted approaches, horses are the most commonly used animals in therapeutic approaches toward patients [6]. When examining thousands of years of history, no matter how much the environmental conditions change, there has always been an intense relationship between societies and horses [57]. In the literature review on the therapeutic use of horses, the concept of AAT is under two headings: therapeutic riding and hippo-therapy. These concepts are named differently as both methods are different but basically with the same goal [58].
\nAlthough there is a belief that horses were tamed and ridden and used in the treatment of the human beings in B.C., there is no definite evidence on this subject [59]. Looking at history and the use of horses as therapeutic agents, horse riding was considered as a physically during exercise in the sixteenth and seventeenth centuries. This aspect was also observed during the 29 rehabilitation of war veterans after the World War II [58]. The use of horses for disabled people has been intensified since the middle of the twentieth century. The best example regarding this was the treatment process, which resulted in Lis Hartel, professional horse-rider, participating in the Olympics and winning a medal while losing lower extremity functions due to polio. After this excellent success, equestrian federations have been established in many developed countries, mainly in England, and AATs are being covered under universal health insurance [60].
\nHippo-therapy, one of the commonly used methods of therapeutic intervention, is derived from the ancient Greek word “Hyppos.” With this method, horses can be used to develop or rehabilitate the individual’s physical, sensory, cognitive, and social functions through the use of horseback movements. Since 2010, American Hippo-therapy Association has created a conceptual framework that includes sensory integration, including dynamic systems theory and motor learning. This conceptual framework takes into account the natural rhythm or movement of the horse that can affect the participants’ neurological, motor, vestibular, sensory, and functional considerations to achieve the intended goals or outcomes [61].
\nChoosing the appropriate horse for the therapy session helps the individual to meet the rehabilitation needs with the individual and the horse feeling more comfortable. The features of an ideal therapy horse are an average age of 10–12 years, an average height of 150–160 cm to help control horses and riders and side holders to about 45° tilt (the stepping stones will get harder as the angle of the bog is lowered), and being calm and gentile [6, 60]. The sessions with hippo therapy, which consist of meeting, warming, working, relaxation, and farewell, are planned by interdisciplinary professionals. Hippo-therapist, occupational therapist, physiotherapist, special education specialist, private horse instructors, and volunteers who have been educated about hippo therapy may be included in the rehabilitation sessions in menaj [61].
\nAs a treatment strategy, hippo therapy may primarily be dependent on the theory of sensory integration because the movement of the horse provides a sensory experience for the rider. The role of therapists is to determine the amount of sensory stimulation and the input [61]. For example, walking slowly cannot be enough incentive to allow the rider to join a relative. On the other hand, brisk walking or jogging can increase the attention span. In addition, riding bareback can help the rider get the maximum possible proprioceptive input. As an alternative approach, stirrups (used with a saddle or backpack) can help proprioceptive input by gravity on the hard surface. Sans, Fortney, and Willenbring [71] argue about this approach of sensory integration as a rider. In addition, this internal drive can be further improved through the connection between the rider and the horse.
\nAt a hippo-therapy session, the horse changes motion by an average of 2000 steps, which means that the rider is also taking 2000 strokes—about 2000 muscle contractions. It has been proved that the increased number of repetitions support motor learning. Therefore, the increase in the number of repetitions due to hippo therapy is the most important parameter supporting the development of static-dynamic balance, weight transfer, motor planning, and motor skill in the direction of the individual’s motor learning principles [62]. During hippo-therapy intervention, following the provision of a suitable position for the rider, the three planes are prepared in accordance with the principles of movement, rhythm, motor learning, and motivation. It has a positive effect on coordination, reaction time, sensory processing, respiratory control, motor planning, and postural control [6, 62]. This multifunctional approach helps to increase the positive effect of the therapy and success of the therapy.
\nOccupational therapy is a client-centered approach to these individuals in rehabilitation practices. The assessment and intervention of occupational therapy are aimed to improve the participation in their daily living activities more meaning and oriented [63]. Occupational therapists use a lot of approaches in their practice to improve quality of life and well-being in their patients. A range of target areas that can be addressed with the help of therapy animals are listed in the book for AAT interventions for OT: motor skills (gross and fine motor), neuro-musculoskeletal skills (range of motion, strength, balance), sensory functioning (tactile, visual, auditory), cognitive skills (orientation, attention, executive functions), weight bearing, communication skills (expression and acculturation language, cooperation), psychosocial skills (well-being, motivation), perception processing skills (body perception, depth perception, spatial relationships), and respiratory function (diaphragm force, positioning) [6, 64].
\nAccording to OTs’ views and perceptions of evidence-based practice, AAT is one of the methods used in rehabilitation. Some researchers have investigated the impact of AAT on elderly participants who were diagnosed with psychiatric, physical, and developmental disabilities in long-term care settings [65]. Van Fleet and his colleagues describe an animal-supported occupational therapy as a learning process in which a professional therapist carries out a therapy session, using a dog, to facilitate the development of the skills needed by the child to have an independent function in self-help, playgrounds. A therapy dog may become part of the learning process when learning everyday tasks related to the animal [66]. OTs may add a wrist weight to gain strength from the weak arm or use a customized brush with a special handle to help the child hold the brush. Thus, the child becomes more motivated and excited to participate in the treatment. Thus, this method helps OTs, and the child can to reach the child’s treatment goals more quickly and easily [67]. In another study, AAT was also applied on patients with post-traumatic stress disorder generally seen in personnel during military service; AAT was found to provide positive benefits. It was also observed that new gained in combat veterans learned new skills using trained dogs [68].
\nDogs are a popular choice for many occupational therapists. OTs showed that treatment with dogs, which are often preferred for treatment, has improved social skills, motivation, having an interest in the environment, and self-awareness of children with autism spectrum who had behavioral problems [6]. A study performed on OTs found that senior citizens in a walking program at an assisted living facility walked further when with a dog than when they walked alone, indicating the potential value of pets in physical conditioning [69]. Due to the earlier studies mentioned, the OTs believed AAT impacted individuals through internal responses to the animal and thorough responses to the external environment. On the other hand, horses proved to be effective in treatment programs, especially for physically disabled people. Among the reasons for preferring the horse in these types of patients include; it can be said that walking on the horse can feel like as the walking accent, walking distance can be adjusted by the therapist or rider if necessary, and positive feeling can increase the motivation of the person [6, 70].
\nIn almost all studies on AAT, animal interaction increased motivation of individuals:
Those who refuse therapy may come to therapy sessions more often and easily when they know that animals are present.
Interaction with animals raises morale of long-term care residents.
People feel better socially people feel better about themselves the idea of ownership of animals and the responsibility for care given to them increases the daily devotion
Sense, motor, perception, cognitive, and social skills improve.
Participation in functioning and daily living activities are facilitated.
OT should focus on the use and participation of meaningful activities to improve the quality of life of an individual in AAT intervention. For these purposes, it is aimed to develop correct posture and walking pattern, mobility of the pelvis and hip region, head and trunk control, muscle tone and strength, sense regulation, social communication, self-confidence and empathy, motor and cognitive skills. It is thought that the ability of individuals to improve their skills, function, and quality of life can be improved by pet ownership, care of animals, and regular interaction during therapy.
\nThe frequency of use of the AAT and AAA in the field of rehabilitation for the last 10 years has been rapidly increasing. Animal-supported approaches from different countries and disciplines showed positive effects on sensory, emotional, and cognitive functions, especially the physical structure and functions of individuals at different ages and diagnoses. OTs emphasize the effectiveness of this method in studies conducted in the field of occupational therapy. At the same time, we believe more qualitative and quantitative research and more detailed studies are still needed and OT’s and OT intervention programs focusing on therapeutic use of animals in rehabilitation must continue.
\nCardiac problems are one of the most important problems across the globe. According to autopsy studies, heart disease has increased since the 1960s due to a rise in the frequency of coronary atherosclerosis with resultant coronary heart disease. The number of CVD deaths in India each year is anticipated to increase from 2.26 to 4.77 million between the years 1990 and 2020. The coronary heart disease frequency rates in India have fluctuated from 1.6 to 7.4% in rural populations whereas from 1 to 13.2% in urban populations during the last several decades [1]. Heart disease claims the lives of about 17 lakh individuals in India each year, and the number is estimated to rise to 2.3 crores by 2030. This rise is linked to an increase in smoking and dietary changes, resulting in higher blood cholesterol levels. The symptoms like angina, chest pain, difficulty breathing, edema, fatigue, and lightheadedness may indicate a heart problem or heart attack. Heart attack can lead to cardiac arrest, which occurs when the heart’s rhythm is disrupted, or the heart stops beating, and the body can no longer function [2].
Any disorder that affects the cardiovascular system is alluded to as heart disease [3]. Heart disease comes in various forms, each of which affects the heart and blood arteries in distinct ways. The most typical kinds of heart disease are coronary artery disease, arrhythmia, heart valve disease, and heart failure [4]. Coronary artery disease is the most noticeable type of heart disease. It happens when plaque accumulates in the arteries that deliver blood to the heart. It can cause a reduction in blood flow to your heart muscle, preventing it from receiving the oxygen it requires. Atherosclerosis, often known as artery hardening, is the most common cause of the illness. Arrhythmia refers to an improper beating of the heart [5]. It happens when the electrical impulses that regulate the heartbeat do not even function properly. As a result, the heart may beat excessively fast, too slowly, or in an irregular pattern. Heart valve disease occurs when a heart valve is damaged [6]. Infectious diseases such as rheumatic fever, congenital heart disease, excessive blood pressure, coronary artery disease are all causes of heart valve disorders. Heart failure does not imply that the heart has ceased to beat. A condition in which the heart is not pumping blood as efficiently as it should be to satisfy the body’s demands. There are some more heart diseases like pericardial disease, myocardial infarction [7], cardiomyopathy, mitral valve regurgitation, congenital heart disease, etc.
Over the last several decades, the rapid advancement of cardiology has profoundly changed the natural course of cardiac patients. Cardiac care has evolved, with technology playing an increasingly significant role. With the appropriate technology and artificial intelligence (AI) and machine learning, cardiac care providers have been motivated to improve treatment methods [8]. Then there’s remote care that enables electrocardiogram (ECG) diagnosis [9], which uses cloud technology and Bluetooth-enabled cardiac devices to test the parameters and send them back to healthcare practitioners without attending the clinic. Some emerging technologies used every day in cardiology are transcatheter mitral and tricuspid valve interventions, artificial intelligence, wearable devices, big data, structured reporting, robots in the cath lab, virtual and augmented reality, FFR technologies, holographic procedural navigation in the Cath Lab, etc. [10].
There are many cardiac implantable electronic devices like pacemakers, implanted cardioverter defibrillators (ICDs), biventricular pacemakers, and cardiac loop recorders, which are used to control or monitor irregular heartbeats in persons with specific heart rhythm problems and heart failure. An implanted cardioverter-defibrillator is a device that can do cardioversion, defibrillation, and cardiac pacing. ICD is capable of rectifying the majority of life-threatening cardiac arrhythmias. A pacemaker is a device that is implanted beneath the skin and communicates with the heart through electrical leads. Pacemakers are used to treat bradycardia, a condition where the heart beats too slowly (less than 60 times per minute). The pacemaker sends electrical pulses to the heart to maintain it beating normally. A biventricular pacemaker is a compact, battery-operated device and light. This gadget aids with the proper pumping of your heart. It also protects from harmful cardiac arrhythmias. An implantable loop recorder is a heart-monitoring device implanted beneath the chest skin. It has a variety of applications. Searching for reasons of fainting, palpitations, very rapid or slow heartbeats, and hidden rhythms that might cause strokes are among the most prevalent. Computer-aided diagnosis (CAD) [11] refers to software that helps clinicians understand medical images. The radiologist or other medical expert must assess and evaluate a large amount of data in a short amount of time using imaging modalities such as X-ray, MRI, and ultrasound diagnostics. The Kurt Rossmann Laboratories for Radiologic Image Research in the Department of Radiology at the University of Chicago began large-scale systematic research and development of several CAD methods in the early 1980s. The idea of computer-aided design was established in 1966 and has been completely implemented since 1980.
Nowadays, computer-aided diagnosis has become a contentious research topic in medical imaging and diagnostic radiology research. CAD technology aids in the improvement of the performance of radiologists in increasing productivity by cost-effectively enhancing sensitivity rate. CAD can improve image diagnostic accuracy by detecting illnesses that are too premature to be detected by naked eyes. It enables early detection, which can lead to better treatment results. Computer-aided detection is a relatively new advancement in the area of breast imaging that aims to increase the throughput of radiologists to identify diseases like breast cancer [12] even at an early stage. In recent times, computer-aided diagnosis is used to diagnose acute lymphoblastic leukemia, which suggested a solution to the flaws in manual diagnosis techniques. Even ECG-based computer-aided diagnosis [13] is also used for cardiovascular diseases which have the potential to improve diagnosis accuracy while also lowering costs.
Medical images nowadays play a crucial role in the identification and diagnosis of awide range of disorders. To aid in the interpretation of medical images, a variety of computer-aided detection and diagnosis technologies have recently been developed in order to achieve a more reliable and accurate diagnosis. CT, MR imaging, digital radiography, biomagnetism, and optical range sensing are examples of imaging systems that take advantage of sophisticated computer technology.
The real-life problem with manual experimentation is that manual diagnostic procedures are time-consuming, less accurate, and prone to mistakes due to different human variables such as stress, exhaustion, fatigue, and so forth. As a result, many automated techniques have been developed to combat the flaws in manual diagnostic approaches. When compared to manual diagnosis procedures, these computer-aided technologies are faster, more dependable, more efficient, more standardization and more accurate. Computer-aided diagnosis (CAD) aids in the calculation of computational and statistical features that people cannot gather visually or intuitively. Computer-assisted diagnosis also reduces the reliance on the operator in ultrasonic imaging and makes the diagnosis procedure reproducible. Interference testing and 3D animations are simple to accomplish in computer-aided diagnosis [14].
Machine learning has been applied in a variety of fields all over the world and the health industry is no exception. On the other hand, deep learning is part of the family of machine learning algorithms relying on representation and artificial neural networks are being utilized for the analysis of medical data. For quite some time, these algorithms were used to assess patients’ status with respect to the image or non-image-based medical data acquired using new generation medical equipment. These developments are attributable to the emergence of new CAD systems known as knowledge-based systems, including expertise or knowledge. As a result, the modern CAD systems include some intelligence [15]. The major job of the software related to these systems nowadays is to automate the analytical phases. To ensure that components and assemblies achieve design standards, CAD software is used to make computer modeling, fit them together, and simulate their performance. Because design reviews, conducted by specialists, evaluate if changes should be made, the analytical phases of the design process are repeated (design synthesis). Design synthesis may be done immediately with AI-based technologies without the need for a separate design review, and they are correctly implemented.
Based on the recent advancements, computer-aided diagnosis is used to diagnose heart abnormalities such as arrhythmias and heart blockages using electrocardiogram (ECG) signal analysis [16]. Although electrocardiography (ECG) is affordable and commonly available, ECG abnormalities are not specific for the diagnosis of congestive heart failure (CHF) which is the inability of the heart to efficiently circulate blood throughout the body without a rise in intracardiac pressure. Based on the ECG, a well-designed computer-aided detection (CAD) system for CHF might possibly eliminate subjectivity and give a quantitative evaluation for better decision-making.
Cardiologists and medical practitioners frequently utilize ECG to assess heart health. The difficulty in identifying and classifying distinct waveforms and morphologies in ECG signals is the major issue with manual analysis. This task is both time-consuming and error-prone for a human. Cardiovascular illnesses are the leading cause of mortality worldwide, accounting for around one-third of all fatalities. Millions of individuals, for example, suffer from irregular heartbeats, which can be fatal in some circumstances. As a result, precise and low-cost arrhythmic heartbeat diagnosis is extremely desirable.
Many research in the literature investigated the utilization of machine learning approaches to reliably detect abnormalities in ECG data to solve the drawbacks present in human analysis. Pre-processing, like passing through bandpass or high pass filter, is used in most of these methods to prepare the signal to be compatible for machine-based analysis. The handcrafted features, which are typically statistical summarizations of signal windows, are then retrieved from these signals and employed in subsequent processing. For the last categorization task, conduct an analysis.
In terms of the conclusion, for ECG, traditional machine learning algorithms [2] like support vector machines, multi-layer perceptrons, decision trees, and other methods of analysis were used previously. Automated feature extraction and representation approaches have been shown to be more scalable and capable of producing more accurate predictions, according to current machine learning research. In this study, we are going to elaborate on a few of the new emerging and compatible technologies and their applications.
The rest of the article has been organized in the following manner. First, Section 2 provides a brief theoretical and mathematical background related to this domain of study which is followed by the problem statement in Section 3. Next, Section 4 discusses about the significance of noise removal with stages of data processing. Section 5 gives a brief survey about the recent state-of-the-art techniques related to automated signal processing of ECG signals that is followed by the promising experimental results reported in the recent literature. Finally, Section 7 concludes this chapter.
In signal processing [17], several mathematical methods like sampling frequency, Nyquist filtering, Fourier analysis series and transform,
The reduction of a continuous-time signal to a discrete-time signal is known as sampling and the sampling frequency represents the number of samples per second collected from a continuous signal to create a discrete or digital signal. There are few applications of the sampling process. The sampling process is utilized in music recordings to ensure sound quality. The sampling technique is also used to convert analog to discrete data. It is also used in speech recognition systems, radar and radio navigation, sensor data evaluation, modulation and demodulation, and pattern recognition systems.
The sampling frequency [18] or sampling rate
If a continuous-time signal has no frequency components greater than a sampling rate of
A Nyquist filter is an electrical filter that equalizes the visual characteristics of TV receivers. In receivers, a Nyquist filter is utilized to equalize the low and high-frequency components of the VF signal. It plays an essential role in the creation of n bandlimited pulses in wired and wireless communication systems to ensure minimal inter symbol interference. Its principal application is as a pulse-shaping filter. Nyquist filters are a form of multi-rate finite impulse response filter that is also known as
The following equation indicates the impulse response of a Nyquist filter
where,
The following equation satisfies the
where,
The frequency responses of all
The Fourier series is a periodic function made up of harmonically compatible sinusoids that are integrated together using a weighted summation. The Fourier series is an infinite series that can be used to solve several forms of differential equations. It’s mainly composed of an infinite sum of sines and cosines, and it’s valuable for evaluating periodic functions since it’s periodic. The Fourier series is widely utilized in telecommunications systems for voice signal modulation and demodulation.
The Fourier transform is a technique for transforming time-domain signals to frequency-domain signals. The Fourier transform is a useful image processing method for decomposing an image into sine and cosine components. The image in the Fourier or frequency domain is represented by the output of the transformation, whereas the spatial domain equivalent is represented by the input image. It’s utilized in electrical circuit design, solving differential equations, signal processing, signal analysis, image processing, and filtering, among other things.
The Fourier transform is a mathematical approach for converting a time function,
The Fourier transform of a sequence is represented as:
where
It can also be written as:
As
The analysis equation of forward Fourier transform is:
On the other hand, the synthesis equation of inverse Fourier transform is:
The bilateral
The unilateral
Fourier transform and
A system’s Fourier transform and
The pole-zero plot is a valuable tool for relating a system’s Frequency domain and
Pole-zero plot can be expressed as the following equation:
where the numerator and denominator are both polynomials in
The electrocardiogram (ECG) signal is a representation of the electrical impulses of the heart that can be seen from the strategic points of the human body. It can be visually depicted by a quasi-periodic voltage signal. ECG refers to a 12-lead ECG recorded while laying down and electrodes or sticky patches are put on the body surface and often over the chest and limbs to record a standard surface ECG. These electrode wires are linked to a 12-lead ECG machine which records data from 12 distinct locations on the body’s surface. The aggregate amplitude of the heart’s electrical potential is then monitored and recorded over a period of time from those distinct angles (“leads”).
The graphical representation of the heart’s electrical activity is formed by analyzing numerous electrodes in Figure 1(a). There are three types of leads: limb augmented limb, and precordial or chest. Three limb leads and three augmented limb leads are organized in the coronal plane like the spokes of a wheel, and six precordial leads or chest leads are organized in the perpendicular transverse plane. In three-dimensional space, each of the 12 ECG leads represents a distinct direction of cardiac activation. The conventional ECG leads are denoted as lead I, II, III, aVF, aVR, aVL, V1, V2, V3, V4, V5, and V6. The limb leads are I, II, III, aVR, aVL, and aVF whereas the precordial leads are V1, V2, V3, V4, V5, and V6.
12 leads ECG. a) Signals from 12 Leads ECG [
The 12-lead ECG is typically made up of 10 electrodes linked to the body, each monitoring a distinct electrical potential difference. The 10 electrodes in a 12-lead ECG are RA, RL, LA, LL, V1, V2, V3, V4, V5, and V6. Each of the 10 electrodes has a different placement as shown in Figure 1(b). RA is used to place on the right arm and similarly, LA is used to place on the left arm. RL is located in the lower end of the inner portion of the calf muscle on the right leg, similarly, LL is placed in the same standard position but on the left leg. V1 is placed in the fourth intercostal space (between ribs 4 and 5) immediate right of the sternum. V2 is placed in the fourth intercostal space (between ribs 4 and 5) immediate left of the sternum. V3 is placed between leads V2 and V4 where V4 is placed in the fifth intercostal space (between ribs 5 and 6) in the midclavicular line. On the other hand, V5 and V6 are placed in the left anterior axillary line and midaxillary line, respectively. The electrodes which are located on the limbs are called limb leads which are leads I, II, and III. Lead I refer to the voltage difference between LA and RA, that is, Lead I = LA-RA. Similarly, Lead II denotes the voltage difference between LL and RA, that is, Lead II = LL-RA. And Lead III denotes the voltage between LL and LA, that is, Lead III = LL-LA.
Lastly, a PQRST complex is part of an ECG complex which is shown in Figure 2. The P wave is produced by the sinoatrial node which is the heart’s pacemaker and implies atrial depolarization in an ECG complex. The atrioventricular node generates the QRS wave. Ventricular depolarization is represented by the QRS, while ventricular repolarization is indicated by the T wave.
PQRST waveform [
In biology, neural networks develop the structure of animal brains, where the phrase “artificial neural networks” comes from. It is widely used in deep learning algorithms. An artificial neural network (ANN) [23] generally consists of three layers, namely, the input layer, hidden layer, and output layer. The hidden layers are present in-between input and output layers. It executes all the calculations to find hidden features and patterns. A shallow neural network consists of only one hidden layer and a deep neural network consists of multiple hidden layers. Generally, each node in one layer is linked to every other node in the next layer. By increasing the number of hidden layers, the network becomes deeper. This architecture is demonstrated in Figure 3.
Architecture of a general ANN [
Based on the concept of ANNs, a convolutional neural network (CNN) [25] was formulated which is a deep learning method that can take an image as input and learn some filters that can be used to extract essential features from those images. The brain is the source of inspiration for convolutional neural networks. CNN performs a linear mathematical procedure known as a convolution in the several hidden layers between an input and output layer. The general mathematical expression of convolution operation is provided in the following equation:
where
CNN’s have the benefit of being able to construct an internal demonstration of a two-dimensional image. This enables the model to learn position and scale in different data formats, which is essential when working with images.
A recurrent neural network (RNN) [26] is a form of artificial neural network which is designed to operate with time series, analyzing temporal and sequential data. It’s one of the algorithms responsible for the incredible advances in deep learning over the last few years. RNN can handle inputs/outputs of varying lengths. The idea of “memory” in RNNs is used to store the states or information of earlier inputs in order to generate the sequence’s next output. It has the ability to store or memorize historical information.
Long short term memory (LSTM) [27] is a type of recurrent neural network and LSTM networks are well-suited to categorize, processing, and generating predictions based on time series data as there might be delays of undetermined duration between critical occurrences in a time series. LSTMs were designed to explode gradients and solve the problem of vanishing gradients that can occur while training standard RNNs.
LSTM uses the concept of gates. It has three gates which are input gate, forget gate, and output gate. The input gate determines what new information will be stored in the cell state. The forget gate determines what information to throw away from the cell state whereas the output gate is used to activate the LSTM block’s final output. In LSTM, output of the gates are operated with sigmoid activation functions, which calculates a value between 0 and 1, which is usually rounded to either 0 or 1 depending upon a predetermined threshold. “0” indicates that the gates are blocking everything and “1” denotes gates that enable everything to pass through it. The LSTM gates have the following equations:
where,
The cell state, candidate cell state, and final output equations are given as follows:
where,
The architecture of LSTM at any timestamp
Graphical representation of LSTM unit [
Bidirectional LSTMs [29] are a kind of LSTM that can be used to increase model performance on sequence classification issues. Bidirectional long-short term memory is the process of allowing any neural network to store sequence information in both backward (future to past) and forward (forward to future) directions. BI-LSTM is typically used when sequence to sequence activities are required. Text classification, speech recognition, and forecasting models can all benefit from using this type of network. Figure 5 shows the architecture of a BI-LSTM.
Graphical representation of bi-directional LSTM unit [
Before the invention of CAD, diagnosis used to be done manually and manual diagnostic procedures were time-consuming, less accurate. In the manual diagnostic procedures, there might be errors in the calculation of computational and statistical features. To counteract the faults in manual diagnostic procedures, deep learning has been introduced to diagnosis. CAD application has heightened the diagnostic performance of non-expert radiologists. Regardless of radiologist expertise, the fundamental benefit of CAD is the minimum false-negative rate and enhanced sensitivity. CAD technologies are faster, more dependable, more accurate and also help to improve in the calculation of computational and statistical features [31]. In this regard, this study focuses on speculating about some of the valuable technologies and trying to approach a conventional solution.
Noise is an undesirable signal which disrupts the original message signal and causes the message signal’s parameters to be altered. Noise distorts the message and hinders it from being understood in an intended manner. When there is loud, distracting noise that disrupts the communication assimilation process, comprehension suffers.
There is no signal without noise. The signal strength may be affected or aided by noise. Noise can cause signal distortion, which is most noticeable in agitated receivers. Both analog and digital systems suffer from noise, which diminishes their performance. Noise degrades the quality of the received signal in analog systems. Noise reduces the overall performance of a digital system because it necessitates retransmission of data packets or additional coding to recover data in the event of an error. The most prevalent and evident issue produced by signal noise is the distortion of the processed signal, which causes inaccurate interpretation or display of a process state by the equipment. Unusual signal noise can cause an apparent signal loss. Noise filtering is incorporated into most current electrical devices. However, in excessively loud circumstances, this filter may not be sufficient, resulting in the device getting no signal and no connection.
The presence of noise can make it difficult or impossible to identify a representative ECG signal. Noises in the ECG signal can lead to incorrect interpretation. In the ECG signal, there are primarily two kinds of noise. Electromyogram noise, additive white Gaussian noise, and power line interference are examples of high-frequency noises. Power line interference distorts the amplitude, duration, and shape of low-amplitude local waves of the ECG signal. Baseline wandering is an example of low-frequency noise. Baseline wandering alters the ECG signal’s ST-segment and LF components.
Noise can be reduced by keeping the signal wires as short as possible or by keeping the wires away from electrical machinery. By using differential inputs, noise can be reduced from both wires. Noise also can be reduced by filtering the signal or by using an integrating A-D converter to reduce mains frequency interference.
There are various ECG denoising techniques [32] that are being used to reduce the noise from signals. Some ECG denoising techniques are EMD-based models, deep-learning-based models, wavelet-based models, sparsity-based models, Bayesian-filter-based models, hybrid models, discrete wavelet transform, etc.
The discrete wavelet transform is a digital processing computational technique that allows for electrical noise with a higher signal-to-noise ratio than lock-in amplifier equipment. A discrete wavelet transform decomposes a signal into a number of sets, each set including a time series of coefficients that describe the signal’s time evolution in the associated frequency band.
The process of converting raw data into a comprehensible format is known as data preprocessing. Dealing with raw data is not suitable, thus this is a key stage in data mining. Before using machine learning or data mining methods, make sure the data is of high quality. In every brain-computer interface-based application, preprocessing data is a necessary and significant step. It checks the accuracy, completeness, believability, consistency, interpretability, timeliness of the data. It assists with the removal of undesirable artifacts from the data and prepares it for subsequent processing.
Peimankar et al. [33] proposed a deep learning model for real-time segmentation of heartbeats which might be utilized in real-time telehealth diagnostic systems. The proposed technique integrates a CNN and an LSTM model to predict and analyze the onset, peak, and offset of various heartbeat waveforms such as the P-wave, QRS complex, T-wave, and no wave. The proposed model is also known as DENS-ECG model. Using 5-fold cross-validation, this model is trained and evaluated on a dataset of 105 ECGs with a length of 15 min each. It attains an average sensitivity and accuracy of 97.95 and 95.68%, respectively. In addition, the method is calibrated on an unknown dataset to assess how robust it is at detecting QRS with a sensitivity of 99.61% and accuracy of 99.52%. This model illustrates the combined CNN-LSTM model’s adaptability and accuracy in delineating ECG signals. The accuracy of the proposed DENS-ECG model in recognizing ECG waveforms leaves the door open for cardiologists to apply this algorithm in-house to evaluate ECG recordings and diagnose cardiac arrhythmias. This model is provided in Figure 6.
Flowchart of the proposed DENS-ECG model [
In Figure 6, noise reduction refers to the filtering of the ECG signals to reduce noise and remove baseline wanders. In the segmentation, the ECG signals are divided into 1000-sample chunks and sent into the model as input. Then the segmented ECG signals are split into two sets to separate the testing set from a non-testing set. This model used a 5-fold cross-validation technique to provide a more trustworthy performance in terms of interpretability. The model consists of eight layers, including an input layer, three 1D convolution layers, two BiLSTM layers, and a dropout layer. And the Adam optimization algorithm is used to validate the algorithm, which is radically different from the steepest gradient descent (SGD) optimization technique and achieved higher performance on the validation. The trained model is tested on 26 unseen test records from the QTDB dataset to assess the classifier’s performance. Furthermore, the model is evaluated for QRS detection on the unexplored MITDB dataset.
Jambukia et al. [34] represented an overview of ECG classification into arrhythmia categories and stated that classification of electrocardiogram (ECG) signals plays a crucial role in the monitoring heart diseases as early and precise diagnosis of arrhythmia types is essential for monitoring cardiac disorders and selecting the best treatment option for a patient. The survey outlines the challenges of ECG classification and provides a comprehensive overview of preprocessing approaches, ECG databases, feature extraction techniques, ANN-based classifiers, and performance measures for evaluating the classifiers’ accuracy. According to the survey, many researchers have worked on ECG signal classification. They have used different pre-processing techniques, various feature extraction techniques, and classifiers. For ECG categorization, the majority of the researchers used the MIT-BIH arrhythmia database. A. Dallali et al. used DWT to extract the RR interval and then used Z score to normalize it. They classified ECG beats using FCM. They achieved a 99.05% accuracy rate. RR interval and R point position are two characteristics retrieved using DWT. FCM was used for pre-classification, while 3-layer MLPNN was used for final classification. They were able to reach a 99.99% accuracy rate.
Saadatnejad et al. [35] proposed an ECG classification model, which was suggested for continuous cardiac detection on wearable devices with limited processing resources. This model is demonstrated in Figure 7 in detail. The model works in such a way that the incoming computerized ECG data were first split into heartbeats and their RR interval while wavelet characteristics were extracted. The ECG signal as well as the extracted characteristics were then put into two RNN-based models that categorized every heartbeat. After that, the two outputs were combined to create the final categorization for every pulse. The suggested method fits the temporal criteria for continuous and real-time execution on wearable devices. Unlike many compute-intensive deep-learning-based techniques, the proposed methodology is accurate and lightweight, allowing wearable devices to have continuous monitoring with accurate LSTM-based ECG categorization having negligible computing expenses while running indefinitely on wearable devices with modest processing capability.
The proposed algorithm of LSTM-based ECG classification model [
Ribeiro et al. [36] had proposed an end-to-end DNN competent of accurately identifying six ECG abnormalities in S12L-ECG examinations, with diagnostic performance comparable to that of medical residents and students. This DNN model trained on data from the Clinical Outcomes in Digital Electrocardiology research which included over 2 million labeled tests analyzed by the Telehealth Network of Minas Gerais. The DNN surpassed cardiology resident medical practitioners in detecting six different types of abnormalities in 12-lead ECG recordings with F1 scores over 80% and specificity exceeding 95%. These results suggest that DNN-based ECG analysis, which was previously tested in a single-lead scenario, generalizes well to 12-lead examinations, bringing the technology closer to practical use. This model has the potential to lead to more accurate automated diagnosis and better clinical practice. Even professional assessment of complex and borderline cases appears to be essential in this future scenario, the implementation of such automatic interpretation by a DNN algorithm may increase the population’s access to this fundamental and valuable diagnostic test. Figure 8 shows the deep learning model used in this work.
The DNN architecture used for ECG classification [
In Figure 8, the Conv, BN, and dense imply the convolution, batch normalization, and the fully connected layers whereas the ReLU and
Figure 9a and b demonstrate the DENS-ECG model’s confusion matrices for the 5-fold CV and test set, respectively. The no wave class has the majority of incorrect cases in all three classes which are P-wave, QRS, and T-wave or it can be said that the model does not make significant errors in classifying the three major classes (P-wave, QRS, and T-wave). The minimal discrepancy between the 5-fold CV and test outcomes indicates that the model has been effectively trained and does not have an overfitting problem.
Confusion matrix [
As demonstrated in Figure 10 the performance plot, the DENS-ECG model performs similarly to other models in QRS detection with 99.61% of sensitivity and 99.52% of precision. The wavelet-based model proposed by Martinez et al. has the best performance in terms of sensitivity and accuracy of 99.8 and 99.86%, respectively followed by Kim and Shin’s proposed model. The postulated DENS-ECG model performed similarly to the well-known Pan and Tompkins’s QRS detection model but it outperformed the QRS detection methods proposed by Poll et al.
Comparison of DENS-ECG and various deep model architectures’ classification performance on the test set [
In [35], the classification ECG signals from heartbeat were classified into both 7 and 5 arrhythmia classes, respectively. For 5-classification problems, the heartbeats are divided into five categories by the Association for Advancement of Medical Instrumentation (AAMI). normal (N), supraventricular (S) ectopic, ventricular (V) ectopic, fusion (F), and unknown (Q) beats are the four types of an ectopic heartbeat. Further, the class N is divided into three more classes in the 7-classification to improve resolution by isolating the two conduction anomalies known as left bundle branch block (L) and right bundle branch block (R). Figure 11 represent the confusion matrix of 7 and 5-class classification problem, respectively where the former model is capable of effectively distinguishing L and R from N.
Confusion matrix [
As shown in Figure 12, Ribeiro et al. [36] has compared DNN’s performance indexes to the average performance of 4th-year cardiology residents, 3rd-year emergency residents, and 5th-year medical students. The performance of the DNN on the test set is demonstrated in the above accuracy plot. The above-shown figure shows that the performance of DNN which exceeds human performance. In most cases, the accuracy of DNN on the data set is more than 95%.
Comparison of performance indexes of DNN and the average performance of cardiology students on the test set [
Finally, the work of Jambukia et al. [34] presents a survey on the performance of various works present in the literature which are based on ECG signal categorization utilizing different pre-processing approaches, feature extraction techniques, and classifiers. Figure 13 presents the plot of the accuracy of different ECG classification techniques which have used the MIT-BIH arrhythmia database over time.
Comparison of the accuracy of the different ECG classification techniques [
Health issues in the human race are increasing day by day and cardiac issues are one of the most common diseases which has been noticed in the past few decades. Therefore, many technologies have been introduced and CAD is the most emerging technology to diagnose cardiac issues or solve heart-related diseases. Furthermore, deep learning has played an important role in the area of computer-aided diagnosis (CAD). From the above discussion, it can be observed that various algorithms or methods have performed pretty well in the field of cardiovascular disease detection. This indicates that deep learning in cardiac signal processing has an unbounded scope in the research field for enhancing CAD and getting more accurate and cost-effective and fast output.
The authors declare no conflict of interest or delete this entire section.
ECG | electrocardiogram |
CVD | cardiovascular disease |
AI | artificial intelligence |
ICD | International Classification of Diseases |
CAD | computer-aided design |
CT | computed tomography |
CHF | congestive heart failure |
ANN | artificial neural network |
CNN | convolutional neural network |
RNN | recurrent neural network |
LSTM | long short-term memory |
BI-LSTM | bi-directional long short-term memory |
DNN | deep neural networks |
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\\n\\nPolicy last updated: 2016-06-09
\\n"}]'},components:[{type:"htmlEditorComponent",content:"In each instance of a possible Conflict of Interest, IntechOpen aims to disclose the situation in as transparent a way as possible in order to allow readers to judge whether a particular potential Conflict of Interest has influenced the Work of any individual Author, Editor, or Reviewer. IntechOpen takes all possible Conflicts of Interest into account during the review process and ensures maximum transparency in implementing its policies.
\n\nA Conflict of Interest is a situation in which a person's professional judgment may be influenced by a range of factors, including financial gain, material interest, or some other personal or professional interest. For IntechOpen as a publisher, it is essential that all possible Conflicts of Interest are avoided. Each contributor, whether an Author, Editor, or Reviewer, who suspects they may have a Conflict of Interest, is obliged to declare that concern in order to make the publisher and the readership aware of any potential influence on the work being undertaken.
\n\nA Conflict of Interest can be identified at different phases of the publishing process.
\n\nIntechOpen requires:
\n\nCONFLICT OF INTEREST - AUTHOR
\n\nAll Authors are obliged to declare every existing or potential Conflict of Interest, including financial or personal factors, as well as any relationship which could influence their scientific work. Authors must declare Conflicts of Interest at the time of manuscript submission, although they may exceptionally do so at any point during manuscript review. For jointly prepared manuscripts, the corresponding Author is obliged to declare potential Conflicts of Interest of any other Authors who have contributed to the manuscript.
\n\nCONFLICT OF INTEREST – ACADEMIC EDITOR
\n\nEditors can also have Conflicts of Interest. Editors are expected to maintain the highest standards of conduct, which are outlined in our Best Practice Guidelines (templates for Best Practice Guidelines). Among other obligations, it is essential that Editors make transparent declarations of any possible Conflicts of Interest that they might have.
\n\nAvoidance Measures for Academic Editors of Conflicts of Interest:
\n\nFor manuscripts submitted by the Academic Editor (or a scientific advisor), an appropriate person will be appointed to handle and evaluate the manuscript. The appointed handling Editor's identity will not be disclosed to the Author in order to maintain impartiality and anonymity of the review.
\n\nIf a manuscript is submitted by an Author who is a member of an Academic Editor's family or is personally or professionally related to the Academic Editor in any way, either as a friend, colleague, student or mentor, the work will be handled by a different Academic Editor who is not in any way connected to the Author.
\n\nCONFLICT OF INTEREST - REVIEWER
\n\nAll Reviewers are required to declare possible Conflicts of Interest at the beginning of the evaluation process. If a Reviewer feels he or she might have any material, financial or any other conflict of interest with regards to the manuscript being reviewed, he or she is required to declare such concern and, if necessary, request exclusion from any further involvement in the evaluation process. A Reviewer's potential Conflicts of Interest are declared in the review report and presented to the Academic Editor, who then assesses whether or not the declared potential or actual Conflicts of Interest had, or could be perceived to have had, any significant impact on the review itself.
\n\nEXAMPLES OF CONFLICTS OF INTEREST:
\n\nFINANCIAL AND MATERIAL
\n\nNON-FINANCIAL
\n\nAuthors are required to declare all potentially relevant non-financial, financial and material Conflicts of Interest that may have had an influence on their scientific work.
\n\nAcademic Editors and Reviewers are required to declare any non-financial, financial and material Conflicts of Interest that could influence their fair and balanced evaluation of manuscripts. If such conflict exists with regards to a submitted manuscript, Academic Editors and Reviewers should exclude themselves from handling it.
\n\nAll Authors, Academic Editors, and Reviewers are required to declare all possible financial and material Conflicts of Interest in the last five years, although it is advisable to declare less recent Conflicts of Interest as well.
\n\nEXAMPLES:
\n\nAuthors should declare if they were or they still are Academic Editors of the publications in which they wish to publish their work.
\n\nAuthors should declare if they are board members of an organization that could benefit financially or materially from the publication of their work.
\n\nAcademic Editors should declare if they were coauthors or they have worked on the research project with the Author who has submitted a manuscript.
\n\nAcademic Editors should declare if the Author of a submitted manuscript is affiliated with the same department, faculty, institute, or company as they are.
\n\nPolicy last updated: 2016-06-09
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Presently he is working as a associate professor in the Dept of Prosthodontics, Rural Dental College, Loni and maintains a successful private practice specialising in Implantology at Rahata.\n\nEmail: drdeepak_mvikhe@yahoo.com..................",institutionString:null,institution:{name:"Pravara Institute of Medical Sciences",country:{name:"India"}}},{id:"204110",title:"Dr.",name:"Ahmed A.",middleName:null,surname:"Madfa",slug:"ahmed-a.-madfa",fullName:"Ahmed A. Madfa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204110/images/system/204110.jpg",biography:"Dr. Madfa is currently Associate Professor of Endodontics at Thamar University and a visiting lecturer at Sana'a University and University of Sciences and Technology. He has more than 6 years of experience in teaching. His research interests include root canal morphology, functionally graded concept, dental biomaterials, epidemiology and dental education, biomimetic restoration, finite element analysis and endodontic regeneration. Dr. Madfa has numerous international publications, full articles, two patents, a book and a book chapter. Furthermore, he won 14 international scientific awards. Furthermore, he is involved in many academic activities ranging from editorial board member, reviewer for many international journals and postgraduate students' supervisor. Besides, I deliver many courses and training workshops at various scientific events. Dr. Madfa also regularly attends international conferences and holds administrative positions (Deputy Dean of the Faculty for Students’ & Academic Affairs and Deputy Head of Research Unit).",institutionString:"Thamar University",institution:null},{id:"210472",title:"Dr.",name:"Nermin",middleName:"Mohammed Ahmed",surname:"Yussif",slug:"nermin-yussif",fullName:"Nermin Yussif",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/210472/images/system/210472.jpg",biography:"Dr. Nermin Mohammed Ahmed Yussif is working at the Faculty of dentistry, University for October university for modern sciences and arts (MSA). Her areas of expertise include: periodontology, dental laserology, oral implantology, periodontal plastic surgeries, oral mesotherapy, nutrition, dental pharmacology. She is an editor and reviewer in numerous international journals.",institutionString:"MSA University",institution:null},{id:"204606",title:"Dr.",name:"Serdar",middleName:null,surname:"Gözler",slug:"serdar-gozler",fullName:"Serdar Gözler",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204606/images/system/204606.jpeg",biography:"Dr. Serdar Gözler has completed his undergraduate studies at the Marmara University Faculty of Dentistry in 1978, followed by an assistantship in the Prosthesis Department of Dicle University Faculty of Dentistry. Starting his PhD work on non-resilient overdentures with Assoc. Prof. Hüsnü Yavuzyılmaz, he continued his studies with Prof. Dr. Gürbüz Öztürk of Istanbul University Faculty of Dentistry Department of Prosthodontics, this time on Gnatology. He attended training programs on occlusion, neurology, neurophysiology, EMG, radiology and biostatistics. In 1982, he presented his PhD thesis \\Gerber and Lauritzen Occlusion Analysis Techniques: Diagnosis Values,\\ at Istanbul University School of Dentistry, Department of Prosthodontics. As he was also working with Prof. Senih Çalıkkocaoğlu on The Physiology of Chewing at the same time, Gözler has written a chapter in Çalıkkocaoğlu\\'s book \\Complete Prostheses\\ entitled \\The Place of Neuromuscular Mechanism in Prosthetic Dentistry.\\ The book was published five times since by the Istanbul University Publications. Having presented in various conferences about occlusion analysis until 1998, Dr. Gözler has also decided to use the T-Scan II occlusion analysis method. Having been personally trained by Dr. Robert Kerstein on this method, Dr. Gözler has been lecturing on the T-Scan Occlusion Analysis Method in conferences both in Turkey and abroad. Dr. Gözler has various articles and presentations on Digital Occlusion Analysis methods. He is now Head of the TMD Clinic at Prosthodontic Department of Faculty of Dentistry , Istanbul Aydın University , Turkey.",institutionString:"Istanbul Aydin University",institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"240870",title:"Ph.D.",name:"Alaa Eddin Omar",middleName:null,surname:"Al Ostwani",slug:"alaa-eddin-omar-al-ostwani",fullName:"Alaa Eddin Omar Al Ostwani",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/240870/images/system/240870.jpeg",biography:"Dr. Al Ostwani Alaa Eddin Omar received his Master in dentistry from Damascus University in 2010, and his Ph.D. in Pediatric Dentistry from Damascus University in 2014. Dr. Al Ostwani is an assistant professor and faculty member at IUST University since 2014. \nDuring his academic experience, he has received several awards including the scientific research award from the Union of Arab Universities, the Syrian gold medal and the international gold medal for invention and creativity. Dr. Al Ostwani is a Member of the International Association of Dental Traumatology and the Syrian Society for Research and Preventive Dentistry since 2017. He is also a Member of the Reviewer Board of International Journal of Dental Medicine (IJDM), and the Indian Journal of Conservative and Endodontics since 2016.",institutionString:"International University for Science and Technology.",institution:{name:"Islamic University of Science and Technology",country:{name:"India"}}},{id:"42847",title:"Dr.",name:"Belma",middleName:null,surname:"Işik Aslan",slug:"belma-isik-aslan",fullName:"Belma Işik Aslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/42847/images/system/42847.jpg",biography:"Dr. Belma IşIk Aslan was born in 1976 in Ankara-TURKEY. After graduating from TED Ankara College in 1994, she attended to Gazi University, Faculty of Dentistry in Ankara. She completed her PhD in orthodontic education at Gazi University between 1999-2005. Dr. Işık Aslan stayed at the Providence Hospital Craniofacial Institude and Reconstructive Surgery in Michigan, USA for three months as an observer. She worked as a specialist doctor at Gazi University, Dentistry Faculty, Department of Orthodontics between 2005-2014. She was appointed as associate professor in January, 2014 and as professor in 2021. Dr. Işık Aslan still works as an instructor at the same faculty. She has published a total of 35 articles, 10 book chapters, 39 conference proceedings both internationally and nationally. Also she was the academic editor of the international book 'Current Advances in Orthodontics'. She is a member of the Turkish Orthodontic Society and Turkish Cleft Lip and Palate Society. She is married and has 2 children. Her knowledge of English is at an advanced level.",institutionString:"Gazi University Dentistry Faculty Department of Orthodontics",institution:null},{id:"178412",title:"Associate Prof.",name:"Guhan",middleName:null,surname:"Dergin",slug:"guhan-dergin",fullName:"Guhan Dergin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178412/images/6954_n.jpg",biography:"Assoc. Prof. Dr. Gühan Dergin was born in 1973 in Izmit. He graduated from Marmara University Faculty of Dentistry in 1999. He completed his specialty of OMFS surgery in Marmara University Faculty of Dentistry and obtained his PhD degree in 2006. In 2005, he was invited as a visiting doctor in the Oral and Maxillofacial Surgery Department of the University of North Carolina, USA, where he went on a scholarship. Dr. Dergin still continues his academic career as an associate professor in Marmara University Faculty of Dentistry. He has many articles in international and national scientific journals and chapters in books.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178414",title:"Prof.",name:"Yusuf",middleName:null,surname:"Emes",slug:"yusuf-emes",fullName:"Yusuf Emes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178414/images/6953_n.jpg",biography:"Born in Istanbul in 1974, Dr. Emes graduated from Istanbul University Faculty of Dentistry in 1997 and completed his PhD degree in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery in 2005. He has papers published in international and national scientific journals, including research articles on implantology, oroantral fistulas, odontogenic cysts, and temporomandibular disorders. Dr. Emes is currently working as a full-time academic staff in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery.",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"192229",title:"Ph.D.",name:"Ana Luiza",middleName:null,surname:"De Carvalho Felippini",slug:"ana-luiza-de-carvalho-felippini",fullName:"Ana Luiza De Carvalho Felippini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192229/images/system/192229.jpg",biography:null,institutionString:"University of São Paulo",institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"256851",title:"Prof.",name:"Ayşe",middleName:null,surname:"Gülşen",slug:"ayse-gulsen",fullName:"Ayşe Gülşen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256851/images/9696_n.jpg",biography:"Dr. Ayşe Gülşen graduated in 1990 from Faculty of Dentistry, University of Ankara and did a postgraduate program at University of Gazi. \nShe worked as an observer and research assistant in Craniofacial Surgery Departments in New York, Providence Hospital in Michigan and Chang Gung Memorial Hospital in Taiwan. \nShe works as Craniofacial Orthodontist in Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi, Ankara Turkey since 2004.",institutionString:"Univeristy of Gazi",institution:null},{id:"255366",title:"Prof.",name:"Tosun",middleName:null,surname:"Tosun",slug:"tosun-tosun",fullName:"Tosun Tosun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255366/images/7347_n.jpg",biography:"Graduated at the Faculty of Dentistry, University of Istanbul, Turkey in 1989;\nVisitor Assistant at the University of Padua, Italy and Branemark Osseointegration Center of Treviso, Italy between 1993-94;\nPhD thesis on oral implantology in University of Istanbul and was awarded the academic title “Dr.med.dent.”, 1997;\nHe was awarded the academic title “Doç.Dr.” (Associated Professor) in 2003;\nProficiency in Botulinum Toxin Applications, Reading-UK in 2009;\nMastership, RWTH Certificate in Laser Therapy in Dentistry, AALZ-Aachen University, Germany 2009-11;\nMaster of Science (MSc) in Laser Dentistry, University of Genoa, Italy 2013-14.\n\nDr.Tosun worked as Research Assistant in the Department of Oral Implantology, Faculty of Dentistry, University of Istanbul between 1990-2002. \nHe worked part-time as Consultant surgeon in Harvard Medical International Hospitals and John Hopkins Medicine, Istanbul between years 2007-09.\u2028He was contract Professor in the Department of Surgical and Diagnostic Sciences (DI.S.C.), Medical School, University of Genova, Italy between years 2011-16. \nSince 2015 he is visiting Professor at Medical School, University of Plovdiv, Bulgaria. \nCurrently he is Associated Prof.Dr. at the Dental School, Oral Surgery Dept., Istanbul Aydin University and since 2003 he works in his own private clinic in Istanbul, Turkey.\u2028\nDr.Tosun is reviewer in journal ‘Laser in Medical Sciences’, reviewer in journal ‘Folia Medica\\', a Fellow of the International Team for Implantology, Clinical Lecturer of DGZI German Association of Oral Implantology, Expert Lecturer of Laser&Health Academy, Country Representative of World Federation for Laser Dentistry, member of European Federation of Periodontology, member of Academy of Laser Dentistry. Dr.Tosun presents papers in international and national congresses and has scientific publications in international and national journals. He speaks english, spanish, italian and french.",institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"171887",title:"Prof.",name:"Zühre",middleName:null,surname:"Akarslan",slug:"zuhre-akarslan",fullName:"Zühre Akarslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/171887/images/system/171887.jpg",biography:"Zühre Akarslan was born in 1977 in Cyprus. She graduated from Gazi University Faculty of Dentistry, Ankara, Turkey in 2000. \r\nLater she received her Ph.D. degree from the Oral Diagnosis and Radiology Department; which was recently renamed as Oral and Dentomaxillofacial Radiology, from the same university. \r\nShe is working as a full-time Associate Professor and is a lecturer and an academic researcher. \r\nHer expertise areas are dental caries, cancer, dental fear and anxiety, gag reflex in dentistry, oral medicine, and dentomaxillofacial radiology.",institutionString:"Gazi University",institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"256417",title:"Associate Prof.",name:"Sanaz",middleName:null,surname:"Sadry",slug:"sanaz-sadry",fullName:"Sanaz Sadry",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256417/images/8106_n.jpg",biography:null,institutionString:null,institution:null},{id:"272237",title:"Dr.",name:"Pinar",middleName:"Kiymet",surname:"Karataban",slug:"pinar-karataban",fullName:"Pinar Karataban",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/272237/images/8911_n.png",biography:"Assist.Prof.Dr.Pınar Kıymet Karataban, DDS PhD \n\nDr.Pınar Kıymet Karataban was born in Istanbul in 1975. After her graduation from Marmara University Faculty of Dentistry in 1998 she started her PhD in Paediatric Dentistry focused on children with special needs; mainly children with Cerebral Palsy. She finished her pHD thesis entitled \\'Investigation of occlusion via cast analysis and evaluation of dental caries prevalance, periodontal status and muscle dysfunctions in children with cerebral palsy” in 2008. She got her Assist. Proffessor degree in Istanbul Aydın University Paediatric Dentistry Department in 2015-2018. ın 2019 she started her new career in Bahcesehir University, Istanbul as Head of Department of Pediatric Dentistry. In 2020 she was accepted to BAU International University, Batumi as Professor of Pediatric Dentistry. She’s a lecturer in the same university meanwhile working part-time in private practice in Ege Dental Studio (https://www.egedisklinigi.com/) a multidisciplinary dental clinic in Istanbul. Her main interests are paleodontology, ancient and contemporary dentistry, oral microbiology, cerebral palsy and special care dentistry. She has national and international publications, scientific reports and is a member of IAPO (International Association for Paleodontology), IADH (International Association of Disability and Oral Health) and EAPD (European Association of Pediatric Dentistry).",institutionString:null,institution:null},{id:"202198",title:"Dr.",name:"Buket",middleName:null,surname:"Aybar",slug:"buket-aybar",fullName:"Buket Aybar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/202198/images/6955_n.jpg",biography:"Buket Aybar, DDS, PhD, was born in 1971. She graduated from Istanbul University, Faculty of Dentistry, in 1992 and completed her PhD degree on Oral and Maxillofacial Surgery in Istanbul University in 1997.\nDr. Aybar is currently a full-time professor in Istanbul University, Faculty of Dentistry Department of Oral and Maxillofacial Surgery. She has teaching responsibilities in graduate and postgraduate programs. Her clinical practice includes mainly dentoalveolar surgery.\nHer topics of interest are biomaterials science and cell culture studies. She has many articles in international and national scientific journals and chapters in books; she also has participated in several scientific projects supported by Istanbul University Research fund.",institutionString:null,institution:null},{id:"260116",title:"Dr.",name:"Mehmet",middleName:null,surname:"Yaltirik",slug:"mehmet-yaltirik",fullName:"Mehmet Yaltirik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/260116/images/7413_n.jpg",biography:"Birth Date 25.09.1965\r\nBirth Place Adana- Turkey\r\nSex Male\r\nMarrial Status Bachelor\r\nDriving License Acquired\r\nMother Tongue Turkish\r\n\r\nAddress:\r\nWork:University of Istanbul,Faculty of Dentistry, Department of Oral Surgery and Oral Medicine 34093 Capa,Istanbul- TURKIYE",institutionString:null,institution:null},{id:"172009",title:"Dr.",name:"Fatma Deniz",middleName:null,surname:"Uzuner",slug:"fatma-deniz-uzuner",fullName:"Fatma Deniz Uzuner",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/172009/images/7122_n.jpg",biography:"Dr. Deniz Uzuner was born in 1969 in Kocaeli-TURKEY. After graduating from TED Ankara College in 1986, she attended the Hacettepe University, Faculty of Dentistry in Ankara. \nIn 1993 she attended the Gazi University, Faculty of Dentistry, Department of Orthodontics for her PhD education. After finishing the PhD education, she worked as orthodontist in Ankara Dental Hospital under the Turkish Government, Ministry of Health and in a special Orthodontic Clinic till 2011. Between 2011 and 2016, Dr. Deniz Uzuner worked as a specialist in the Department of Orthodontics, Faculty of Dentistry, Gazi University in Ankara/Turkey. In 2016, she was appointed associate professor. Dr. Deniz Uzuner has authored 23 Journal Papers, 3 Book Chapters and has had 39 oral/poster presentations. She is a member of the Turkish Orthodontic Society. Her knowledge of English is at an advanced level.",institutionString:null,institution:null},{id:"332914",title:"Dr.",name:"Muhammad Saad",middleName:null,surname:"Shaikh",slug:"muhammad-saad-shaikh",fullName:"Muhammad Saad Shaikh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Jinnah Sindh Medical University",country:{name:"Pakistan"}}},{id:"315775",title:"Dr.",name:"Feng",middleName:null,surname:"Luo",slug:"feng-luo",fullName:"Feng Luo",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Sichuan University",country:{name:"China"}}},{id:"423519",title:"Dr.",name:"Sizakele",middleName:null,surname:"Ngwenya",slug:"sizakele-ngwenya",fullName:"Sizakele Ngwenya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"419270",title:"Dr.",name:"Ann",middleName:null,surname:"Chianchitlert",slug:"ann-chianchitlert",fullName:"Ann Chianchitlert",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"419271",title:"Dr.",name:"Diane",middleName:null,surname:"Selvido",slug:"diane-selvido",fullName:"Diane Selvido",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"419272",title:"Dr.",name:"Irin",middleName:null,surname:"Sirisoontorn",slug:"irin-sirisoontorn",fullName:"Irin Sirisoontorn",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"355660",title:"Dr.",name:"Anitha",middleName:null,surname:"Mani",slug:"anitha-mani",fullName:"Anitha Mani",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"355612",title:"Dr.",name:"Janani",middleName:null,surname:"Karthikeyan",slug:"janani-karthikeyan",fullName:"Janani Karthikeyan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"334400",title:"Dr.",name:"Suvetha",middleName:null,surname:"Siva",slug:"suvetha-siva",fullName:"Suvetha Siva",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}}]}},subseries:{item:{id:"41",type:"subseries",title:"Water Science",keywords:"Water, Water resources, Freshwater, Hydrological processes, Utilization, Protection",scope:"