Advances in Electrodermal Activity Processing with Applications for Mental Health

Alberto Greco, M.Eng., Ph.D., is currently a Research Fellow of Bioengineering at the University of Pisa, Italy. He received his master degree in Biomedical Engineering in 2010 and the Ph.D. degree in Automation, Robotics, and Bioengineering in 2015 from the University of Pisa (Italy) with a thesis about the processing and the modelling of the electrodermal activity. In 2014, He has been a Visiting Fellow at the School of Computer Science and Electronic Engineering at the University of Essex, U.K. where He deeply studied convex optimization methods applied to physiological signal modelling. His research interests include statistical biomedical signal processing, machine learning, physiological modeling, and wearable systems for physiological monitoring. Applications include the assessment of the autonomic nervous system and central nervous system, affective computing and the assessment of mood and consciousness disorders. He is author of several international scientific contributions in these fields published in peer-reviewed international journals, conference proceedings, and book. He has been involved in several European research projects. Gaetano Valenza, M.Eng., Ph.D., is currently an Assistant Professor of Bioengineering at the University of Pisa, Pisa, Italy. In 2009, He started working at the Bioengineering and Robotics Research Centre "E. Piaggio" in Pisa and, in 2011, He joined the Neuro-Cardiovascular Signal Processing unit within the Neuroscience Statistics Research Laboratory at Massachusetts Institute of Technology, Cambridge, USA. In 2013, He received the Ph.D. degree in Automation, Robotics, and Bioengineering from the University of Pisa and, in the same year, was appointed as a Research Fellow at Harvard Medical School/ Massachusetts General Hospital, Boston, USA. His research interests include statistical and nonlinear biomedical signal and image processing, cardiovascular and neural modeling, and wearable systems for physiological monitoring. Applications of his research include the assessment of autonomic nervous system activity on cardiovascular control, brain-heart interactions, affective computing, assessment of mood and mental/neurological disorders. He is author of more than 100 international scientific contributions in these fields published in peer-reviewed international journals, conference proceedings, books and book chapters, and is official reviewer of more than sixty international scientific journals, and research funding agencies. He has been involved in several international research projects, and currently is the scientific co-coordinator of the European collaborative project H2020-PHC-2015-689691-NEVERMIND. Dr. Valenza has been guest editor and member of the editorial board of several international scientific journals. Enzo Pasquale Scilingo, Ph.D.is an Associate Professor in Electronic and Information Bioengineering at the University of Pisa. He received the Laurea Degree in Electronic Engineering from the University of Pisa, Italy and the Ph.D.degree in Bioengineering from the University of Milan, in 1995 and 1998 respectively. For two years he was postdoctoral fellow with the Italian National Research Council and for two years post-doctoral fellow at Information Engineering Department of the University of Pisa. Currently, he is pursuing his research work mainly at the Research Center "E. Piaggio". He has several teaching activities, he is supervisor of several PhD students and he is leading the laboratory Biolab at the Information Engineering Department . He coordinated a European project EC-FP7-ICT-247777 "PSYCHE-Personalised monitoring SYstems for Care in mental Health", and he is currently coordinating the European project H2020-PHC-2015-689691 NEVERMIND - NEurobehavioural predictiVE and peRsonalised Modelling of depressIve symptoms duriNg primary somatic Diseases with ICT-enabled self-managemen

1. Electrodermal Phenomena and Recording Techniques.- 2. Modeling for the Analysis of the EDA.- 3. Evaluation of CDA and CvxEDA models.- 4. Emotions and Mood States: Modeling, Elicitation, and Recognition.- 5. Experimental Applications on Multi-Sensory Affective Stimulation.- 6. Conclusions.

"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)