@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{\textquoteright}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.",
keywords = "Mood assessment, Self-report system, User interface",
author = "Hristo Valev and Tim Leufkens and Corina Sas and Joyce Westerink and Ron Dotsch",
year = "2019",
month = jul,
day = "11",
doi = "10.1007/978-3-030-25872-6_19",
language = "English",
isbn = "978-3-030-25871-9",
series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",
publisher = "Springer",
pages = "231--241",
editor = "Pietro Cipresso and Silvia Serino and Daniela Villani",
booktitle = "Pervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings",
address = "Germany",
note = "9th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2019 ; Conference date: 23-04-2019 Through 24-04-2019",
}