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Autonomic Nervous System Dynamics for Mood and Emotional State Recognition: Wearable Systems, Modeling and Advanced Biosignal Processing

2013
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Release : 2013
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Book Synopsis Autonomic Nervous System Dynamics for Mood and Emotional State Recognition: Wearable Systems, Modeling and Advanced Biosignal Processing by : Gaetano Valenza

Download or read book Autonomic Nervous System Dynamics for Mood and Emotional State Recognition: Wearable Systems, Modeling and Advanced Biosignal Processing written by Gaetano Valenza. This book was released on 2013. Available in PDF, EPUB and Kindle. Book excerpt:

Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition

2013-10-29 Technology & Engineering
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Release : 2013-10-29
Genre : Technology & Engineering
Kind : eBook
Book Rating : 399/5 ( reviews)

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Book Synopsis Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition by : Gaetano Valenza

Download or read book Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition written by Gaetano Valenza. This book was released on 2013-10-29. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Biosignal Processing Challenges in Emotion Recognition for Adaptive Learning

2010 Biomedical engineering
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Release : 2010
Genre : Biomedical engineering
Kind : eBook
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Book Synopsis Biosignal Processing Challenges in Emotion Recognition for Adaptive Learning by : Aniket A. Vartak

Download or read book Biosignal Processing Challenges in Emotion Recognition for Adaptive Learning written by Aniket A. Vartak. This book was released on 2010. Available in PDF, EPUB and Kindle. Book excerpt: User-centered computer based learning is an emerging field of interdisciplinary research. Research in diverse areas such as psychology, computer science, neuroscience and signal processing is making contributions the promise to take this field to the next level. Learning systems built using contributions from these fields could be used in actual training and education instead of just laboratory proof-of-concept. One of the important advances in this research is the detection and assessment of the cognitive and emotional state of the learner using such systems. This capability moves development beyond the use of traditional user performance metrics to include system intelligence measures that are based on current neuroscience theories. These advances are of paramount importance in the success and wide spread use of learning systems that are automated and intelligent. Emotion is considered an important aspect of how learning occurs, and yet estimating it and making adaptive adjustments are not part of most learning systems. In this research we focus on one specific aspect of constructing an adaptive and intelligent learning system, that is, estimation of the emotion of the learner as he/she is using the automated training system. The challenge starts with the definition of the emotion and the utility of it in human life. The next challenge is to measure the co-varying factors of the emotions in a non-invasive way, and find consistent features from these measures that are valid across wide population. In this research we use four physiological sensors that are non-invasive, and establish a methodology of utilizing the data from these sensors using different signal processing tools. A validated set of visual stimuli used worldwide in the research of emotion and attention, called International Affective Picture System (IAPS), is used. A dataset is collected from the sensors in an experiment designed to elicit emotions from these validated visual stimuli. We describe a novel wavelet method to calculate hemispheric asymmetry metric using electroencephalography data. This method is tested against typically used power spectral density method. We show overall improvement in accuracy in classifying specific emotions using the novel method. We also show distinctions between different discrete emotions from the autonomic nervous system activity using electrocardiography, electrodermal activity and pupil diameter changes. Findings from different features from these sensors are used to give guidelines to use each of the individual sensors in the adaptive learning environment.

Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems

2020-11-13 Technology & Engineering
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Release : 2020-11-13
Genre : Technology & Engineering
Kind : eBook
Book Rating : 774/5 ( reviews)

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Book Synopsis Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems by : Luefeng Chen

Download or read book Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems written by Luefeng Chen. This book was released on 2020-11-13. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the key technologies and scientific problems involved in emotional robot systems, such as multimodal emotion recognition (i.e., facial expression/speech/gesture and their multimodal emotion recognition) and emotion intention understanding, and presents the design and application examples of emotional HRI systems. Aiming at the development needs of emotional robots and emotional human–robot interaction (HRI) systems, this book introduces basic concepts, system architecture, and system functions of affective computing and emotional robot systems. With the professionalism of this book, it serves as a useful reference for engineers in affective computing, and graduate students interested in emotion recognition and intention understanding. This book offers the latest approaches to this active research area. It provides readers with the state-of-the-art methods of multimodal emotion recognition, intention understanding, and application examples of emotional HRI systems.

Wearable Computing

2018-04-06 Technology & Engineering
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Release : 2018-04-06
Genre : Technology & Engineering
Kind : eBook
Book Rating : 822/5 ( reviews)

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Book Synopsis Wearable Computing by : Giancarlo Fortino

Download or read book Wearable Computing written by Giancarlo Fortino. This book was released on 2018-04-06. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the most up-to-date research and development on wearable computing, wireless body sensor networks, wearable systems integrated with mobile computing, wireless networking and cloud computing This book has a specific focus on advanced methods for programming Body Sensor Networks (BSNs) based on the reference SPINE project. It features an on-line website (http://spine.deis.unical.it) to support readers in developing their own BSN application/systems and covers new emerging topics on BSNs such as collaborative BSNs, BSN design methods, autonomic BSNs, integration of BSNs and pervasive environments, and integration of BSNs with cloud computing. The book provides a description of real BSN prototypes with the possibility to see on-line demos and download the software to test them on specific sensor platforms and includes case studies for more practical applications. • Provides a future roadmap by learning advanced technology and open research issues • Gathers the background knowledge to tackle key problems, for which solutions will enhance the evolution of next-generation wearable systems • References the SPINE web site (http://spine.deis.unical.it) that accompanies the text • Includes SPINE case studies and span topics like human activity recognition, rehabilitation of elbow/knee, handshake detection, emotion recognition systems Wearable Systems and Body Sensor Networks: from modeling to implementation is a great reference for systems architects, practitioners, and product developers. Giancarlo Fortino is currently an Associate Professor of Computer Engineering (since 2006) at the Department of Electronics, Informatics and Systems (DEIS) of the University of Calabria (Unical), Rende (CS), Italy. He was recently nominated Guest Professor in Computer Engineering of Wuhan University of Technology on April, 18 2012 (the term of appointment is three years). His research interests include distributed computing and networks, wireless sensor networks, wireless body sensor networks, agent systems, agent oriented software engineering, streaming content distribution networks, distributed multimedia systems, GRID computing. Raffaele Gravina received the B.Sc. and M.S. degrees both in computer engineering from the University of Calabria, Rende, Italy, in 2004 and 2007, respectively. Here he also received the Ph.D. degree in computer engineering. He's now a Postdoctoral research fellow at University of Calabria. His research interests are focused on high-level programming methods for WSNs, specifically Wireless Body Sensor Networks. He wrote almost 30 scientific/technical articles in the area of the proposed Book. He is co-founder of SenSysCal S.r.l., a spin-off company of the University of Calabria, and CTO of the wearable computing area of the company. Stefano Galzarano received the B.S. and M.S. degrees both in computer engineering from the University of Calabria, Rende, Italy, in 2006 and 2009, respectively. He is currently pursuing a joint Ph.D. degree in computer engineering with University of Calabria and Technical University of Eindhoven (The Netherlands). His research interests are focused on high-level programming methods for wireless sensor networks and, specifically, novel methods and frameworks for autonomic wireless body sensor networks.

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