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Multiresolution Feature Extraction During Psychophysiological Inference: Addressing Signals Asynchronicity

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Physiological Computing Systems (PhyCS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8908))

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Abstract

Predicting the psychological state of the user using physiological measures is one of the main objectives of physiological computing. While numerous works have addressed this task with great success, a large number of challenges remain to be solved in order to develop recognition approaches that can precisely and reliably feed human-computer interaction systems. This chapter focuses on one of these challenges which is the temporal asynchrony between different physiological signals within one recognition model. The chapter proposes a flexible and suitable method for feature extraction based on empirical optimisation of windows’ latency and duration. The approach is described within the theoretical framework of the psychophysiological inference and its common implementation using machine learning. The method has been experimentally validated (46 subjects) and results are presented. Empirically optimised values for the extraction windows are provided.

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Acknowledgements

This work was supported by NSERC (Natural Sciences and Engineering Research Council of Canada), the Canadian Space Agency and Bell Canada. The authors would like to thank the Bell Web Solutions User Experience Center for providing the eye-tracker system used in this research. We also wish to thank Laurence Dumont for early comments on the manuscript.

Author information

Authors and Affiliations

  1. Tech3Lab, HEC Montréal, Louis-Colin av, Montréal, Canada

    François Courtemanche & Élise L. LeMoyne

  2. Department of Communication, University of Montréal, Édouard-Montpetit blvd, Montréal, Canada

    Aude Dufresne

Authors
  1. François Courtemanche
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  2. Aude Dufresne
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  3. Élise L. LeMoyne
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Corresponding author

Correspondence to François Courtemanche .

Editor information

Editors and Affiliations

  1. IT - Instituto de Telecomunicações, Lisbon, Portugal

    Hugo Plácido da Silva

  2. Medical University Graz, Graz, Austria

    Andreas Holzinger

  3. Liverpool John Moores, Liverpool, Merseyside, United Kingdom

    Stephen Fairclough

  4. ETH Zurich, Zurich, Switzerland

    Dennis Majoe

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Courtemanche, F., Dufresne, A., LeMoyne, É.L. (2014). Multiresolution Feature Extraction During Psychophysiological Inference: Addressing Signals Asynchronicity. In: da Silva, H., Holzinger, A., Fairclough, S., Majoe, D. (eds) Physiological Computing Systems. PhyCS 2014. Lecture Notes in Computer Science(), vol 8908. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45686-6_3

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  • DOI: https://doi.org/10.1007/978-3-662-45686-6_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45685-9

  • Online ISBN: 978-3-662-45686-6

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