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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

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Andreas Holzinger

    1. Medical University of Graz, Graz, Austria

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  2. Alan Pope

    1. NASA Langley Research Center, Hampton, USA

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  3. Hugo Plácido da Silva

    1. IT - Instituto de Telecomunicações, Lisbon, Portugal

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10057)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: PhyCS 2016. PhyCS 2017. PhyCS 2018.

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Table of contents (12 papers)

  1. Front Matter

    Pages i-xx
    Download chapter PDF

  2. Development and Assessment of a Self-paced BCI-VR Paradigm Using Multimodal Stimulation and Adaptive Performance

    • Athanasios Vourvopoulos, André Ferreira, Sergi Bermudez i Badia
    Pages 1-22

  3. Bio-behavioral Modeling of Workload and Performance

    • Jean-François Gagnon, Olivier Gagnon, Daniel Lafond, Mark Parent, Sébastien Tremblay
    Pages 23-38

  4. Simple and Robust Automatic Detection and Recognition of Human Movement Patterns in Tasks of Different Complexity

    • Lisa Gutzeit, Marc Otto, Elsa Andrea Kirchner
    Pages 39-57

  5. From Body Tracking Interaction in Floor Projection Displays to Elderly Cardiorespiratory Training Through Exergaming

    • Afonso Gonçalves, Filipa Nóbrega, Mónica Cameirão, John E. Muñoz, Élvio Gouveia, Sergi Bermudez i Badia
    Pages 58-77

  6. Looking for Emotions on a Single EEG Signal

    • Roylán Quesada-Tabares, Alberto J. Molina-Cantero, José I. Escudero-Fombuena, Manuel Merino-Monge, Isabel M. Gómez-González, Clara Lebrato-Vázquez et al.
    Pages 78-92

  7. Detection of Artifacts Using a Non-invasive BCI on the Basis of Electroencephalography While Utilizing Low-Cost Off-the-Shelf Equipment

    • Patrick Schembri, Richard Anthony, Mariusz Pelc
    Pages 93-109

  8. A Data-Driven Model Based on Support Vector Machine to Identify Chronic Hypertensive and Diabetic Patients

    • Cristina Soguero-Ruiz, Pablo de Miguel-Bohoyo, Inmaculada Mora-Jiménez
    Pages 110-129

  9. Inner Flower: Design and Evaluation of a Tangible Biofeedback for Relaxation

    • Morgane Hamon, Léo Cousin, Rémy Ramadour, Jérémy Frey
    Pages 130-157

  10. Towards Industrial Assistance Systems: Experiences of Applying Multi-sensor Fusion in Harsh Environments

    • Michael Haslgrübler, Bendikt Gollan, Alois Ferscha
    Pages 158-179

  11. Hand Gesture Recognition Based on EMG Data: A Convolutional Neural Network Approach

    • Panagiotis Tsinganos, Bruno Cornelis, Jan Cornelis, Bart Jansen, Athanassios Skodras
    Pages 180-197

  12. Heart Rhythm Qualitative Analysis Using Low-Cost and Open Source Electrocardiography: A Study Based on Atrial Fibrillation Detection

    • Hélio B. M. Lourenço, Víctor Sanfins, Fernando Torgal, Sílvia Ala, Manuel J. C. S. Reis, Hugo P. Silva et al.
    Pages 198-217

  13. Integrating Biocybernetic Adaptation in Virtual Reality Training Concentration and Calmness in Target Shooting

    • John E. Muñoz, Alan T. Pope, Luis E. Velez
    Pages 218-237

  14. Back Matter

    Pages 239-239
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Other volumes

  1. Physiological Computing Systems

Keywords

About this book

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.

Editors and Affiliations

  • Medical University of Graz, Graz, Austria

    Andreas Holzinger

  • NASA Langley Research Center, Hampton, USA

    Alan Pope

  • IT - Instituto de Telecomunicações, Lisbon, Portugal

    Hugo Plácido da Silva

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