Evaluation of a self-report system for assessing mood using facial expressions

Hristo Valev, Tim Leufkens, Corina Sas, Joyce Westerink, Ron Dotsch

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

Uittreksel

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.

TaalEngels
TitelPervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings
RedacteurenSilvia Serino, Daniela Villani, Pietro Cipresso
Plaats van productieCham
UitgeverijSpringer
Pagina's231-241
Aantal pagina's11
ISBN van elektronische versie978-3-030-25872-6
ISBN van geprinte versie978-3-030-25871-9
DOI's
StatusGepubliceerd - 11 jul 2019
Evenement9th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2019 - Buenos Aires, Argentinië
Duur: 23 apr 201924 apr 2019

Publicatie series

NaamLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume288
ISSN van geprinte versie1867-8211

Congres

Congres9th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2019
LandArgentinië
StadBuenos Aires
Periode23/04/1924/04/19

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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 S. Serino, D. Villani, & P. Cipresso (editors), Pervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings (blz. 231-241). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 288). Cham: Springer. DOI: 10.1007/978-3-030-25872-6_19
    Valev, Hristo ; Leufkens, Tim ; Sas, Corina ; Westerink, Joyce ; Dotsch, Ron. / Evaluation of a self-report system for assessing mood using facial expressions. Pervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings. redacteur / Silvia Serino ; Daniela Villani ; Pietro Cipresso. Cham : Springer, 2019. blz. 231-241 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST).
    @inproceedings{dcefdf71435f4dbe8722196d04206992,
    title = "Evaluation of a self-report system for assessing mood using facial expressions",
    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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    Valev, H, Leufkens, T, Sas, C, Westerink, J & Dotsch, R 2019, Evaluation of a self-report system for assessing mood using facial expressions. in S Serino, D Villani & P Cipresso (redactie), Pervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 288, Springer, Cham, blz. 231-241, Buenos Aires, Argentinië, 23/04/19. DOI: 10.1007/978-3-030-25872-6_19

    Evaluation of a self-report system for assessing mood using facial expressions. / Valev, Hristo; Leufkens, Tim; Sas, Corina; Westerink, Joyce; Dotsch, Ron.

    Pervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings. redactie / Silvia Serino; Daniela Villani; Pietro Cipresso. Cham : Springer, 2019. blz. 231-241 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 288).

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

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    AB - 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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    Valev H, Leufkens T, Sas C, Westerink J, Dotsch R. Evaluation of a self-report system for assessing mood using facial expressions. In Serino S, Villani D, Cipresso P, redacteurs, Pervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings. Cham: Springer. 2019. blz. 231-241. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST). Beschikbaar vanaf, DOI: 10.1007/978-3-030-25872-6_19