Abstract
Affective computing has focused on emotion acquisition using techniques of objective (sensors, facial recognition, physiological signals) and subjective measurement (self-report). Each technique has advantages and drawbacks, and a combination of the information generated from each could provide systems more balanced and accurate information about user emotions. However, there are several benefits to self-reporting emotions, over objective techniques: the collected information may be more precise and it is less intrusive to determine. This systematic literature review focuses on analyzing which technologies have been proposed to conduct subjective measurements of emotions through self-report. We aim to understand the state of the art regarding the features of interfaces for emotional self-report, identify the context for which they were designed, and describe several other aspects of the technologies. A SLR was conducted, resulting in 18 selected papers, 13 of which satisfied the inclusion criteria. We identified most existing systems use graphical user interfaces, and there are very few proposals that use tangible user interfaces to self-report emotional information, which may be an opportunity to design novel interfaces, especially for populations with low digital skills, e.g. older adults.
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Acknowledgements
This project was partially funded by CONICYT Chile PhD scholarship, CONICIT and MICIT Costa Rica PhD scholarship and Universidad de Costa Rica, and Fondecyt (Chile) Project No. 1150365.
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Fuentes, C., Gerea, C., Herskovic, V., Marques, M., Rodríguez, I., Rossel, P.O. (2015). User Interfaces for Self-reporting Emotions: A Systematic Literature Review. In: García-Chamizo, J., Fortino, G., Ochoa, S. (eds) Ubiquitous Computing and Ambient Intelligence. Sensing, Processing, and Using Environmental Information. UCAmI 2015. Lecture Notes in Computer Science(), vol 9454. Springer, Cham. https://doi.org/10.1007/978-3-319-26401-1_30
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