This monograph reports on advances in the measurement and study of autonomic nervous system (ANS) dynamics as a source of reliable and effective markers for mood state recognition and assessment of emotional responses. Its primary impact will be in affective computing and the application of emotion-recognition systems. Applicative studies of biosignals such as: electrocardiograms; electrodermal responses; respiration activity; gaze points; and pupil-size variation are covered in detail, and experimental results explain how to characterize the elicited affective levels and mood states pragmatically and accurately using the information thus extracted from the ANS. Nonlinear signal processing techniques play a crucial role in understanding the ANS physiology underlying superficially noticeable changes and provide important quantifiers of cardiovascular control dynamics. These have prognostic value in both healthy subjects and patients with mood disorders. Moreover, Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition proposes a novel probabilistic approach based on the point-process theory in order to model and characterize the instantaneous ANS nonlinear dynamics providing a foundation from which machine “understanding” of emotional response can be enhanced. Using mathematics and signal processing, this work also contributes to pragmatic issues such as emotional and mood-state modeling, elicitation, and non-invasive ANS monitoring. Throughout the text a critical review on the current state-of-the-art is reported, leading to the description of dedicated experimental protocols, novel and reliable mood models, and novel wearable systems able to perform ANS monitoring in a naturalistic environment. Biomedical engineers will find this book of interest, especially those concerned with nonlinear analysis, as will researchers and industrial technicians developing wearable systems and sensors for ANS monitoring.

This book reports on the latest advances in complex and nonlinear cardiovascular physiology aimed at obtaining reliable, effective markers for the assessment of heartbeat, respiratory, and blood pressure dynamics. The chapters describe in detail methods that have been previously defined in theoretical physics such as entropy, multifractal spectra, and Lyapunov exponents, contextualized within physiological dynamics of cardiovascular control, including autonomic nervous system activity. Additionally, the book discusses several application scenarios of these methods. The text critically reviews the current state-of-the-art research in the field that has led to the description of dedicated experimental protocols and ad-hoc models of complex physiology. This text is ideal for biomedical engineers, physiologists, and neuroscientists. This book also: Expertly reviews cutting-edge research, such as recent advances in measuring complexity, nonlinearity, and information-theoretic concepts applied to coupled dynamical systems Comprehensively describes applications of analytic technique to clinical scenarios such as heart failure, depression and mental disorders, atrial fibrillation, acute brain lesions, and more Broadens readers' understanding of cardiovascular signals, heart rate complexity, heart rate variability, and nonlinear analysis

Recent years have seen important developments in the computer and game industry, including the emergence of the concept of serious games. It is hypothesized that tools such as games, virtual reality, or applications for smartphones may foster learning, enhance motivation, promote behavioral change, support psychotherapy, favor empowerment, and improve some cognitive functions. Computers and games may create supports for training or help people with cognitive, emotional, or behavioral change. Games take various formats, from board games to informatics to games with interactive rules of play. Similarly, computer tools may vary widely in format, from self-help or assisted computerized training to virtual reality or applications for smartphones. Some tools that may be helpful for mental health were specifically designed for that goal, whereas others were not. Gamification of computer-related products and games with a numeric format tend to reduce the gap between games and computers tools and increase the conceptual synergy in such fields. Games and computer design share an opportunity for creativity and innovation to help create, specifically design, and assess preventive or therapeutic tools. Computers and games share a design conception that allows innovative approaches to overcome barriers of the real world by creating their own rules. Yet, despite the potential interest in such tools to improve treatment of mental disorders and to help prevent them, the field remains understudied and information is under-disseminated in clinical practice. Some studies have shown, however, that there is potential interest and acceptability of tools that support various vehicles, rationales, objectives, and formats. These tools include traditional games (e.g., chess games), popular electronic games, board games, computer-based interventions specifically designed for psychotherapy or cognitive training, virtual reality, apps for smartphones, and so forth. Computers and games may offer a true opportunity to develop, assess, and disseminate new prevention and treatment tools for mental health and well-being. Currently, there is a strong need for state-of-the-art information to answer questions such as the following: Why develop such tools for mental health and well-being? What are the potential additions to traditional treatments? What are the best strategies or formats to improve the possible impact of these tools? Are such tools useful as a first treatment step? What is the potential of a hybrid model of care that combines traditional approaches with games and/or computers as tools? What games and applications have already been designed and studied? What is the evidence from previous studies? How can such tools be successfully designed for mental health and well-being? What is rewarding or attractive for patients in using such treatments? What are the worldwide developments in the field? Are some protocols under development? What are the barriers and challenges related to such developments? How can these tools be assessed, and how can the way that they work, and for whom, be measured? Are the potential benefits of such products specific, or can these additions be attributed to nonspecific factors? What are the users’ views on such tools? What are the possible links between such tools and social networks? Is there a gap between evidence-based results and market development? Are there any quality challenges? What future developments and studies are needed in the field?

This book reports on the theoretical foundations, fundamental applications and latest advances in various aspects of connected services for health information systems. The twelve chapters highlight state-of-the-art approaches, methodologies and systems for the design, development, deployment and innovative use of multisensory systems and tools for health management in smart city ecosystems. They exploit technologies like deep learning, artificial intelligence, augmented and virtual reality, cyber physical systems and sensor networks. Presenting the latest developments, identifying remaining challenges, and outlining future research directions for sensing, computing, communications and security aspects of connected health systems, the book will mainly appeal to academic and industrial researchers in the areas of health information systems, smart cities, and augmented reality.

This volume offers readers various perspectives and visions for cutting-edge research in ubiquitous healthcare. The topics emphasize large-scale architectures and high performance solutions for smart healthcare, healthcare monitoring using large-scale computing techniques, Internet of Things (IoT) and big data analytics for healthcare, Fog Computing, mobile health, large-scale medical data mining, advanced machine learning methods for mining multidimensional sensor data, smart homes, and resource allocation methods for the BANs. The book contains high quality chapters contributed by leading international researchers working in domains, such as e-Health, pervasive and context-aware computing, cloud, grid, cluster, and big-data computing. We are optimistic that the topics included in this book will provide a multidisciplinary research platform to the researchers, practitioners, and students from biomedical engineering, health informatics, computer science, and computer engineering.

Functional and Clinical Neuroanatomy: A Guide for Health Care Professionals is a comprehensive, yet easy-to read, introduction to neuroanatomy that covers the structures and functions of the central, peripheral and autonomic nervous systems. The book also focuses on the clinical presentation of disease processes involving specific structures. It is the first review of clinical neuroanatomy that is written specifically for nurses, physician assistants, nurse practitioners, medical students and medical assistants who work in the field of neurology. It will also be an invaluable resource for graduate and postgraduate students in neuroscience. With 22 chapters, including two that provide complete neurological examinations and diagnostic evaluations, this book is an ideal resource for health care professionals across a wide variety of disciplines. - Written specifically for "mid-level" providers in the field of neurology - Provides an up-to-date review of clinical neuroanatomy based on the latest guidelines - Provides a logical, step-by-step introduction to neuroanatomy - Offers hundreds of full-color figures to illustrate important concepts - Highlights key subjects in "Focus On" boxes - Includes Section Reviews at critical points in the text of each chapter

Psychophysiological Methods in Language Research: Rethinking Embodiment in Studies of Linguistic Behaviors by Bahiyyih Hardacreis a guide for adopting a transdisciplinary and multidimensional approach to language research. Language research areas that could benefit from psychophysiological methods are first/second/foreign language learning, teaching, use, assessment, performance, anxiety, motivation, attitudes, ideologies, perceptions, and identities, among others. To aid researchers in deciding on a suitable physiological measurement method, this book provides an overview of each of the most popular physiological measurements today, along with their potential applications in language research. Bahiyyih Hardacre explains what each of the physiological methods can tell us, illustrates how each physiological method can inform language research by citing a few language studies that used that particular measurement, and provides information about the appropriate procedures for data collection and data processing.

Neuroscientific research on emotion has developed dramatically over the past decade. The cognitive neuroscience of human emotion, which has emerged as the new and thriving area of 'affective neuroscience', is rapidly rendering existing overviews of the field obsolete. This handbook provides a comprehensive, up-to-date and authoritative survey of knowledge and topics investigated in this cutting-edge field. It covers a range of topics, from face and voice perception to pain and music, as well as social behaviors and decision making. The book considers and interrogates multiple research methods, among them brain imaging and physiology measurements, as well as methods used to evaluate behavior and genetics. Editors Jorge Armony and Patrik Vuilleumier have enlisted well-known and active researchers from more than twenty institutions across three continents, bringing geographic as well as methodological breadth to the collection. This timely volume will become a key reference work for researchers and students in the growing field of neuroscience.

This book includes impactful chapters which present scientific concepts, frameworks, architectures and ideas on sensing technologies and machine learning techniques. These are relevant in tackling the following challenges: (i) the field readiness and use of intrusive sensor systems and devices for capturing biosignals, including EEG sensor systems, ECG sensor systems and electrodermal activity sensor systems; (ii) the quality assessment and management of sensor data; (iii) data preprocessing, noise filtering and calibration concepts for biosignals; (iv) the field readiness and use of nonintrusive sensor technologies, including visual sensors, acoustic sensors, vibration sensors and piezoelectric sensors; (v) emotion recognition using mobile phones and smartwatches; (vi) body area sensor networks for emotion and stress studies; (vii) the use of experimental datasets in emotion recognition, including dataset generation principles and concepts, quality insurance and emotion elicitation material and concepts; (viii) machine learning techniques for robust emotion recognition, including graphical models, neural network methods, deep learning methods, statistical learning and multivariate empirical mode decomposition; (ix) subject-independent emotion and stress recognition concepts and systems, including facial expression-based systems, speech-based systems, EEG-based systems, ECG-based systems, electrodermal activity-based systems, multimodal recognition systems and sensor fusion concepts and (x) emotion and stress estimation and forecasting from a nonlinear dynamical system perspective. This book, emerging from the Special Issue of the Sensors journal on “Emotion and Stress Recognition Related Sensors and Machine Learning Technologies” emerges as a result of the crucial need for massive deployment of intelligent sociotechnical systems. Such technologies are being applied in assistive systems in different domains and parts of the world to address challenges that could not be addressed without the advances made in these technologies.

This book explores Autonomic Nervous System (ANS) dynamics as investigated through Electrodermal Activity (EDA) processing. It presents groundbreaking research in the technical field of biomedical engineering, especially biomedical signal processing, as well as clinical fields of psychometrics, affective computing, and psychological assessment. This volume describes some of the most complete, effective, and personalized methodologies for extracting data from a non-stationary, nonlinear EDA signal in order to characterize the affective and emotional state of a human subject. These methodologies are underscored by discussion of real-world applications in mood assessment. The text also examines the physiological bases of emotion recognition through noninvasive monitoring of the autonomic nervous system. This is an ideal book for biomedical engineers, physiologists, neuroscientists, engineers, applied mathmeticians, psychiatric and psychological clinicians, and graduate students in these fields. This book also: Expertly introduces a novel approach for EDA analysis based on convex optimization and sparsity, a topic of rapidly increasing interest Authoritatively presents groundbreaking research achieved using EDA as an exemplary biomarker of ANS dynamics Deftly explores EDA's potential as a source of reliable and effective markers for the assessment of emotional responses in healthy subjects, as well as for the recognition of pathological mood states in bipolar patients