Artificial Intelligence-Based Brain Computer Interface provides concepts of AI for the modeling of non-invasive modalities of medical signals such as EEG, MRI and FMRI. These modalities and their AI-based analysis are employed in BCI and related applications. The book emphasizes the real challenges in non-invasive input due to the complex nature of the human brain and for a variety of applications for analysis, classification and identification of different mental states. Each chapter starts with a description of a non-invasive input example and the need and motivation of the associated AI methods, along with discussions to connect the technology through BCI.

Major topics include different AI methods/techniques such as Deep Neural Networks and Machine Learning algorithms for different non-invasive modalities such as EEG, MRI, FMRI for improving the diagnosis and prognosis of numerous disorders of the nervous system, cardiovascular system, musculoskeletal system, respiratory system and various organs of the body. The book also covers applications of AI in the management of chronic conditions, databases, and in the delivery of health services.

This book looks at analysis and modelling of active biopotential signal processing. It emphasises the real-time challenges in biomedical signal processing that occur due to the complex and non-stationary nature of signals in a variety of applications for analysis, classification and identification of different states for improvement of healthcare systems. The main focus of the book is on modelling; acquisition of biomedical signals for different disorders; implementation of methodologies and their impact on different cases; case studies and research directions; automatic identification of related disorders; design and simulation examples; and issues and challenges. Overall, the book addresses the real-time challenges in biomedical signal processing used in a variety of applications such as analysis, classification and identification of different disorders in healthcare systems. It is a valuable guide for all researchers and practitioners who are engaged in studies and research in the area of biomedical signals and their applications. 

Key Features

Biopotential signals are often used by physicians to measure the activities of organs and tissues in the human body. This book describes the sources and characteristics of different biopotential signals and provides an understanding of how a range of signals can be modelled and analysed. The resulting information can be used to assist in the identification of disorders such as epilepsy, schizophrenia, PTSD and heart disease, among others. An emphasis is placed on the real challenges in biopotential signal processing due to the complex and non-stationary nature of signals.

Following on from volume one, this book starts with a collection of chapters covering some of the latest developments in electroencephalography (EEG) signal analysis, then moves on to applications of electrocardiography (ECG) and otoscope signals. The volume concludes with a discussion of other monitoring techniques. The chapters include biomedical examples and discussions of how each method can be used to study human organs. It is a valuable guide for all researchers and practitioners who are engaged in studies and research in the area of biomedical signals and their applications.

Key Features

Modern internet-enabled devices and fast communication technologies have ushered in a revolution in sharing of digital images and video. This may be for social reasons or for commercial and industrial applications, where the data is more likely to include sensitive personal or confidential information. In any event, the shared imagery is intended only for the end-user. Attackers can steal this data or manipulate it for their own uses, causing financial and emotional damage to the owners. Many applications generate important information in the form of images and video, where efficient security is critical. This drives the need for advanced security solutions and the need to continuously develop and maintain security measures in an ever-evolving battle against fraud and malicious intent.

There are various techniques employed in protecting digital media and information, such as digital watermarking, cryptography, stenography, data encryption, etc., In addition, sharing platforms and connected nodes themselves may be open to vulnerabilities and can suffer from security breaches. This book reviews present state-of-the-art research related to the security of digital imagery and video, including developments in machine learning applications. It is particularly suited for those that bridge the academic world and industry, and allows readers to understand the security concerns in the multimedia domain by reviewing present and evolving security solutions, their limitations, and future research directions.

Key Features

Modern medicine and healthcare are highly dependent on engineering, employing instrumentation and computer systems to aid investigation, diagnosis, treatment and patient management. The significant developments in the field of computational intelligence, combined with the emergence of high-performance computing is impacting society in many ways, and the health sector is no exception. The interface of high-performance computing, computational intelligence and medical science, has seen the emergence of intelligent medical systems. These systems can provide a deeper insight into many healthcare and medical problems. It can also aid in controlling, analyzing and the management of medical applications and can provide significant improvement in the quality of life and efficacy of clinical treatment. However, the successful application of high-performance computing in medicine requires in-depth knowledge and understanding of medical systems. This book focuses on the advances and applications of high-performance computing for medical systems and provides an insight into the latest developments in the field. It will help readers to understand the high-performance computing research domain as related to intelligent medical systems, its effect on our lives and its present limitations.

Computer vision and image processing-based systems and their applications are already an integral part of modern living and are expected to increase in prevalence and complexity. Vision system provides the ability to handle and examine the large data generated by cameras and make a decision based on the situational requirement. As computational intelligent methods are especially adept at rapidly resolving inexact situations or where there is incomplete knowledge, they are being heavily researched and employed in this space. This merger creates intelligent vision systems, which can be extremely versatile, and this book focusses on the latest developments and current key research areas in the field.

Key Features:

Industry 4.0 is an amalgamation of digital technologies with the industries; it is required for enhancing production, flexibility and scalability in industries. This field of research is a rapidly changing domain. It is also a multifaceted area of research including signal processing, computer vision, artificial intelligence, manufacturing, production engineering, etc. This book brings together professionals from academia and industry to present a review of state of knowledge in the fields of advanced signal and vision processing, the Industrial Internet of Things, AI and machine learning, signal processing for smart manufacturing, cyber-physical systems and intelligent systems for industries as applied to the implementation of Industry 4.0. The book will help readers to understand future needs of industries.

Key Features:

Discussion of various IOT based systems for classification and design strategy of biomedical systems are provided in the book. This book can serve as a pillar for the IOT application in biomedical systems understanding.

Cognitive sensors and associated AI and algorithms are most important components of cognitive science research and studies. This book provides a critical review of the emerging themes of cognitive sensors, how it functions and its applications in a range of disciplines. Volume I includes Sensor Physics, Imaging, Modalities, Pre-processing of images, Problems and Issues in Cognitive Sensing techniques, Cognitive Sensors and IoTs, Psychological, Philosophical and Linguistic Studies of Cognitive Science; Humanoid robots, Industrial Robots and intelligence, Cognitive Sensor Network and applications. This book presents a brilliant introduction to Cognitive Sensors for industrial and academic researchers in sensor science and technology, smart systems, Internet of Things, and biomedical engineering.

Key Features:

In the modern world, sensors and sensor networks are critical features in developing applications for control and automation in engineering and technology. Cognitive Science is a multidisciplinary area of research that covers artificial intelligence, neuroscience, mathematics, philosophy, psychology, linguistics, automated diagnosis etc. Cognitive sensors and associated AI and algorithms are most important components of cognitive science research and studies. This book will provide a review of the emerging theme of cognitive sensors, how it functions and its applications in a range of disciplines.

Volume 2 features Cognitive Sensors in smart healthcare, including appropriate Signal Processing, Filtering, Machine Learning and AI for medical Cognitive Science analysis and applications; Case Studies, Brain Disorder and Stress analysis.

Key Features:

Artificial Intelligence-Based Brain Computer Interface provides concepts of AI for the modeling of non-invasive modalities of medical signals such as EEG, MRI and FMRI. These modalities and their AI-based analysis are employed in BCI and related applications. The book emphasizes the real challenges in non-invasive input due to the complex nature of the human brain and for a variety of applications for analysis, classification and identification of different mental states. Each chapter starts with a description of a non-invasive input example and the need and motivation of the associated AI methods, along with discussions to connect the technology through BCI.

Major topics include different AI methods/techniques such as Deep Neural Networks and Machine Learning algorithms for different non-invasive modalities such as EEG, MRI, FMRI for improving the diagnosis and prognosis of numerous disorders of the nervous system, cardiovascular system, musculoskeletal system, respiratory system and various organs of the body. The book also covers applications of AI in the management of chronic conditions, databases, and in the delivery of health services.

This book looks at analysis and modelling of active biopotential signal processing. It emphasises the real-time challenges in biomedical signal processing that occur due to the complex and non-stationary nature of signals in a variety of applications for analysis, classification and identification of different states for improvement of healthcare systems. The main focus of the book is on modelling; acquisition of biomedical signals for different disorders; implementation of methodologies and their impact on different cases; case studies and research directions; automatic identification of related disorders; design and simulation examples; and issues and challenges. Overall, the book addresses the real-time challenges in biomedical signal processing used in a variety of applications such as analysis, classification and identification of different disorders in healthcare systems. It is a valuable guide for all researchers and practitioners who are engaged in studies and research in the area of biomedical signals and their applications. 

Key Features

Biopotential signals are often used by physicians to measure the activities of organs and tissues in the human body. This book describes the sources and characteristics of different biopotential signals and provides an understanding of how a range of signals can be modelled and analysed. The resulting information can be used to assist in the identification of disorders such as epilepsy, schizophrenia, PTSD and heart disease, among others. An emphasis is placed on the real challenges in biopotential signal processing due to the complex and non-stationary nature of signals.

Following on from volume one, this book starts with a collection of chapters covering some of the latest developments in electroencephalography (EEG) signal analysis, then moves on to applications of electrocardiography (ECG) and otoscope signals. The volume concludes with a discussion of other monitoring techniques. The chapters include biomedical examples and discussions of how each method can be used to study human organs. It is a valuable guide for all researchers and practitioners who are engaged in studies and research in the area of biomedical signals and their applications.

Key Features

Modern internet-enabled devices and fast communication technologies have ushered in a revolution in sharing of digital images and video. This may be for social reasons or for commercial and industrial applications, where the data is more likely to include sensitive personal or confidential information. In any event, the shared imagery is intended only for the end-user. Attackers can steal this data or manipulate it for their own uses, causing financial and emotional damage to the owners. Many applications generate important information in the form of images and video, where efficient security is critical. This drives the need for advanced security solutions and the need to continuously develop and maintain security measures in an ever-evolving battle against fraud and malicious intent.

There are various techniques employed in protecting digital media and information, such as digital watermarking, cryptography, stenography, data encryption, etc., In addition, sharing platforms and connected nodes themselves may be open to vulnerabilities and can suffer from security breaches. This book reviews present state-of-the-art research related to the security of digital imagery and video, including developments in machine learning applications. It is particularly suited for those that bridge the academic world and industry, and allows readers to understand the security concerns in the multimedia domain by reviewing present and evolving security solutions, their limitations, and future research directions.

Key Features

Modern medicine and healthcare are highly dependent on engineering, employing instrumentation and computer systems to aid investigation, diagnosis, treatment and patient management. The significant developments in the field of computational intelligence, combined with the emergence of high-performance computing is impacting society in many ways, and the health sector is no exception. The interface of high-performance computing, computational intelligence and medical science, has seen the emergence of intelligent medical systems. These systems can provide a deeper insight into many healthcare and medical problems. It can also aid in controlling, analyzing and the management of medical applications and can provide significant improvement in the quality of life and efficacy of clinical treatment. However, the successful application of high-performance computing in medicine requires in-depth knowledge and understanding of medical systems. This book focuses on the advances and applications of high-performance computing for medical systems and provides an insight into the latest developments in the field. It will help readers to understand the high-performance computing research domain as related to intelligent medical systems, its effect on our lives and its present limitations.

Computer vision and image processing-based systems and their applications are already an integral part of modern living and are expected to increase in prevalence and complexity. Vision system provides the ability to handle and examine the large data generated by cameras and make a decision based on the situational requirement. As computational intelligent methods are especially adept at rapidly resolving inexact situations or where there is incomplete knowledge, they are being heavily researched and employed in this space. This merger creates intelligent vision systems, which can be extremely versatile, and this book focusses on the latest developments and current key research areas in the field.

Key Features:

Industry 4.0 is an amalgamation of digital technologies with the industries; it is required for enhancing production, flexibility and scalability in industries. This field of research is a rapidly changing domain. It is also a multifaceted area of research including signal processing, computer vision, artificial intelligence, manufacturing, production engineering, etc. This book brings together professionals from academia and industry to present a review of state of knowledge in the fields of advanced signal and vision processing, the Industrial Internet of Things, AI and machine learning, signal processing for smart manufacturing, cyber-physical systems and intelligent systems for industries as applied to the implementation of Industry 4.0. The book will help readers to understand future needs of industries.

Key Features:

Discussion of various IOT based systems for classification and design strategy of biomedical systems are provided in the book. This book can serve as a pillar for the IOT application in biomedical systems understanding.

Cognitive sensors and associated AI and algorithms are most important components of cognitive science research and studies. This book provides a critical review of the emerging themes of cognitive sensors, how it functions and its applications in a range of disciplines. Volume I includes Sensor Physics, Imaging, Modalities, Pre-processing of images, Problems and Issues in Cognitive Sensing techniques, Cognitive Sensors and IoTs, Psychological, Philosophical and Linguistic Studies of Cognitive Science; Humanoid robots, Industrial Robots and intelligence, Cognitive Sensor Network and applications. This book presents a brilliant introduction to Cognitive Sensors for industrial and academic researchers in sensor science and technology, smart systems, Internet of Things, and biomedical engineering.

Key Features:

In the modern world, sensors and sensor networks are critical features in developing applications for control and automation in engineering and technology. Cognitive Science is a multidisciplinary area of research that covers artificial intelligence, neuroscience, mathematics, philosophy, psychology, linguistics, automated diagnosis etc. Cognitive sensors and associated AI and algorithms are most important components of cognitive science research and studies. This book will provide a review of the emerging theme of cognitive sensors, how it functions and its applications in a range of disciplines.

Volume 2 features Cognitive Sensors in smart healthcare, including appropriate Signal Processing, Filtering, Machine Learning and AI for medical Cognitive Science analysis and applications; Case Studies, Brain Disorder and Stress analysis.

Key Features: