Physiological Computing Systems | International Conferences, PhyCS 2016, Lisbon, Portugal, July 27-28, 2016, PhyCS 2017, Madrid, Spain, July 27-28, 2017, PhyCS 2018, Seville, Spain, September 19-21, 2018, Revised and Extended Selected Papers

Andreas Holzinger (u. a.)

ISBN 10: 3030279499 / ISBN 13: 9783030279493

Published by Springer, 2019

About this Item

Physiological Computing Systems | International Conferences, PhyCS 2016, Lisbon, Portugal, July 27-28, 2016, PhyCS 2017, Madrid, Spain, July 27-28, 2017, PhyCS 2018, Seville, Spain, September 19-21, 2018, Revised and Extended Selected Papers | Andreas Holzinger (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xx | Englisch | 2019 | Springer | EAN 9783030279493 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Seller Inventory # 116920779

Bibliographic Details

• Title: Physiological Computing Systems | International Conferences, PhyCS 2016, Lisbon, Portugal, July 27-28, 2016, PhyCS 2017, Madrid, Spain, July 27-28, 2017, PhyCS 2018, Seville, Spain, September 19-21, 2018, Revised and Extended Selected Papers
• Publisher: Springer
• Publication Date: 2019
• Language: English
• ISBN 10: 3030279499
• ISBN 13: 9783030279493
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 15D millimeters 235 millimeters width by 155 millimeters height by 15 millimeters depth
• Weight: 400 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

This book constitutes the proceedings of the Third International Conference on Physiological Computing Systems, PhyCS 2016, held in Lisbon, Portugal, in July 2016.
The 12 papers presented in this volume were carefully reviewed and selected from numerous submissions. They contribute to the understanding of relevant trends of current research on physiological computing systems, including brain-computer interfaces, virtual reality, psychophysiological load assessment in unconstrained scenarios, body tracking and movement pattern recognition, emotion recognition, machine learning applied to diabetes and hypertension, tangible biofeedback technologies, multimodal sensor data fusion, and deep learning for hand gesture recognition.