Editors:
Covers various scientific areas in machine learning, artificial neural networks, social and biometric data for applications in human–computer interactions
Presents recent research in dynamic signal exchanges and demonstrates how these advances can characterize a more friendly human–machine interaction
Proposes approaches to measure and quantify human behavior for the implementation of autonomous, and complex human–computer Interfaces
Considers key aspects of the integration of algorithms and procedures for the recognition of dynamic (faces, speech, gaits, EEGs, brain and speech waves) signals, in anticipation of the implementation of useful applications such as intelligent avatars, interactive dialog systems, and reliable complex autonomous systems for human signal’s detection and identification
Includes contributions from leading authorities in their respective fields
Part of the book series: Smart Innovation, Systems and Technologies (SIST, volume 103)
Conference series link(s): WIRN: Italian Workshop on Neural Nets
Conference proceedings info: WIRN 2017 2017.
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Table of contents (25 chapters)
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Front Matter
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Introduction
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Front Matter
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Dynamics of Signal Exchanges
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Front Matter
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About this book
The book is based on interdisciplinary research on various aspects and dynamics of human multimodal signal exchanges. It discusses realistic application scenarios where human interaction is the focus, in order to
- identify new methods for data processing and data flow coordination through synchronization, and optimization of new encoding features combining contextually enacted communicative signals, and
- develop shared digital data repositories and annotation standards for benchmarking the algorithmic feasibility and successive implementation of believable human–computer interaction (HCI) systems.
This book is a valuable resource for
a. the research community, PhD students, early stage researchers
c. schools, hospitals, and rehabilitation and assisted-living centers
e. the ICT market, and representatives from multimedia industries
Keywords
- Machine Learning Methods
- User Modelling
- Neural Networks
- Artificial Intelligence
- Customer Care
- Situated Human-Computer Interaction (HCI)
- Social Science Scholarship
- Daily Life Activities
- Biometric Data
- Health & Well Being
- Social Signal Processing
- Social Behaviour and Context
- Complex Human-Computer Interfaces
Editors and Affiliations
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Dipartimento di Psicologia, Università della Campania “Luigi Vanvitelli”, Caserta, Italy
Anna Esposito
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Fundació Tecnocampus, Pompeu Fabra University, Mataro, Spain
Marcos Faundez-Zanuy
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Department of Civil, Environmental, Energy, and Material Engineering, University Mediterranea of Reggio Calabria, Reggio Calabria, Italy
Francesco Carlo Morabito
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Dipartimento di Elettronica e Telecomunicazioni, Laboratorio di Neuronica, Politecnico di Torino, Turin, Italy
Eros Pasero
Bibliographic Information
Book Title: Quantifying and Processing Biomedical and Behavioral Signals
Editors: Anna Esposito, Marcos Faundez-Zanuy, Francesco Carlo Morabito, Eros Pasero
Series Title: Smart Innovation, Systems and Technologies
DOI: https://doi.org/10.1007/978-3-319-95095-2
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2019
Hardcover ISBN: 978-3-319-95094-5Published: 27 August 2018
Softcover ISBN: 978-3-030-06976-6Published: 20 December 2018
eBook ISBN: 978-3-319-95095-2Published: 17 August 2018
Series ISSN: 2190-3018
Series E-ISSN: 2190-3026
Edition Number: 1
Number of Pages: XI, 274
Number of Illustrations: 18 b/w illustrations, 65 illustrations in colour