Research Article
Evaluation of a Self-report System for Assessing Mood Using Facial Expressions
@INPROCEEDINGS{10.1007/978-3-030-25872-6_19, author={Hristo Valev and Tim Leufkens and Corina Sas and Joyce Westerink and Ron Dotsch}, title={Evaluation of a Self-report System for Assessing Mood Using Facial Expressions}, proceedings={Pervasive Computing Paradigms for Mental Health. 9th International Conference, MindCare 2019, Buenos Aires, Argentina, April 23--24, 2019, Proceedings}, proceedings_a={MINDCARE}, year={2019}, month={7}, keywords={Mood assessment Self-report system User interface}, doi={10.1007/978-3-030-25872-6_19} }- Hristo Valev
Tim Leufkens
Corina Sas
Joyce Westerink
Ron Dotsch
Year: 2019
Evaluation of a Self-report System for Assessing Mood Using Facial Expressions
MINDCARE
Springer
DOI: 10.1007/978-3-030-25872-6_19
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.