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

ISBN 10: 3030279499 / ISBN 13: 9783030279493

Editore: Springer International Publishing, Springer International Publishing, 2019

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Druck auf Anfrage Neuware - Printed after ordering - 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. Codice articolo 9783030279493

Dati bibliografici

Titolo: Physiological Computing Systems : ...

Casa editrice: Springer International Publishing, Springer International Publishing

Data di pubblicazione: 2019

Legatura: Taschenbuch

Condizione: Neu

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Riassunto:

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.