Advances in Electrodermal Activity Processing with Applications for Mental Health
From Heuristic Methods to Convex Optimization
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Beschreibung
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:
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
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:
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
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 Includes supplementary material: sn.pub/extras
Autor*in
Alberto Greco
Themen in »Advances in Electrodermal Activity Processing with Applications for Mental Health«
Affective Computing Autonomic Nervous System Continuous Deconvolution Analysis Convex Optimization Analysis Mood and Emotion Recognition Physiological Modeling Psychometrics Psychophysiology Statistical Biosignal Processing
Stimmen zu »Advances in Electrodermal Activity Processing with Applications for Mental Health«
“The book presents an appraisal of the state of the art of EDA methodologies and applications, typical analysis tools, and recording means. … The book has well-balanced and highly interdisciplinary content and might be of interest to a large audience, including psychologists, dermatologists, and physicians, or signal processing researchers, mathematicians, engineers, and scientists involved in affective computing. … By its structure and content, the book may serve as a guide to newcomers in psychological science and affective computing.” (Computing Reviews, October, 2017)
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