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Evaluation of a Self-report System for Assessing Mood Using Facial Expressions

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Pervasive Computing Paradigms for Mental Health (MindCare 2019)

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Abstract

Effective and frequent sampling of mood through self-reports could enable a better understanding of the interplay between mood and events influencing it. To accomplish this, we built a mobile application featuring a sadness-happiness visual analogue scale and a facial expression-based scale. The goal is to evaluate, whether a facial expression based scale could adequately capture mood. The method and mobile application were evaluated with 11 participants. They rated the mood of characters presented in a series of vignettes, using both scales. Participants also completed a user experience survey rating the two assessment methods and the mobile interface. Findings reveal a Pearson’s correlation coefficient of 0.97 between the two assessment scales and a stronger preference for the face scale. We conclude with a discussion of the implications of our findings for mood self-assessment and an outline future research.

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Acknowledgment

This work has been supported by AffecTech: Personal Technologies for Affective Health, Innovative Training Network funded by the H2020 People Programme under Marie Skłodowska-Curie grant agreement No. 722022.

Author information

Authors and Affiliations

  1. Philips Research, High Tech Campus 34, 5656 AE, Eindhoven, The Netherlands

    Hristo Valev, Tim Leufkens, Joyce Westerink & Ron Dotsch

  2. Lancaster University, Bailrigg, Lancaster, LA1 4YW, UK

    Hristo Valev & Corina Sas

  3. Eindhoven University of Technology Tu/e, 5600 MB, Eindhoven, The Netherlands

    Tim Leufkens & Joyce Westerink

Authors
  1. Hristo Valev
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  2. Tim Leufkens
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  3. Corina Sas
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  4. Joyce Westerink
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  5. Ron Dotsch
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Corresponding author

Correspondence to Hristo Valev .

Editor information

Editors and Affiliations

  1. IRCCS Istituto Auxologico Italiano, Milan, Italy

    Pietro Cipresso

  2. Department of Clinical Neurosciences, University of Lausanne, Lausanne, Switzerland

    Silvia Serino

  3. Catholic University of the Sacred Heart, Milan, Italy

    Daniela Villani

A Appendix A

A Appendix A

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Valev, H., Leufkens, T., Sas, C., Westerink, J., Dotsch, R. (2019). Evaluation of a Self-report System for Assessing Mood Using Facial Expressions. In: Cipresso, P., Serino, S., Villani, D. (eds) Pervasive Computing Paradigms for Mental Health. MindCare 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 288. Springer, Cham. https://doi.org/10.1007/978-3-030-25872-6_19

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  • DOI: https://doi.org/10.1007/978-3-030-25872-6_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-25871-9

  • Online ISBN: 978-3-030-25872-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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