Abstract
Some people find it difficult to express and recognise emotions through facial expressions. To help these people and to provide a new tool for specialists to use in their therapies with these patients, this paper proposes an imitation game, developed as a mobile app. In this app, the player will see himself on the mobile screen as in a mirror, and he/she will have to imitate the faces that are presented to him/her in order to accumulate points. The app recognises, through the mobile phone’s camera and software libraries, the emotion that the player is expressing and checks whether it matches the one presented. The game has been developed under the supervision of a psychiatrist to guarantee as far as possible its therapeutic usefulness. Among other features, the game collects statistics that can help to identify which emotions are most problematic for the patient, and thus the therapist can track his/her progress. The result is an app that is fun and, most importantly, has a lot of therapeutic potential.
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References
Zichermann, G., Cunningham, C.: Gamification by Design: Implementing Game Mechanics in Web and Mobile Apps. O’Reilly Media, Inc. (2011)
Ekman, P., Friesen, W.V.: Constants across cultures in the face and emotion. J. Pers. Soc. Psychol. 17(2), 124 (1971)
Google Vision AI. https://cloud.google.com/vision?hl=en. Last Accessed 29 Jul 2022
Amazon Rekognition. https://aws.amazon.com/en/rekognition/. Last Accessed 29 Jul 2022
Microsoft Azure Face. https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/index-identity. Last Accessed 29 Jul 2022
MoodMe 4 Emotions Barracuda SDK. https://assetstore.unity.com/packages/tools/ai/moodme-4-emotions-barracuda-sdk-202171. Last Accessed 29 Jul 2022
Van der Vegt, W., Westera, W., Nyamsuren, E., Georgiev, A., Ortiz, I.M.: RAGE architecture for reusable serious gaming technology components. Int. J. Compute. Games Technol. (2016)
Kalantarian, H., Jedoui, K., Washington, P., Wall, D.P.: A mobile game for automatic emotion-labeling of images. IEEE Trans. Games 12(2), 213–218 (2018)
Tan, C.T., Sapkota, H., Rosser, D.: Befaced: a casual game to crowdsource facial expressions in the wild. In: CHI’14 Extended Abstracts on Human Factors in Computing Systems, pp. 491–494 (2014)
Fernández-Sotos, P., García, A.S., Vicente-Querol, M.A., Lahera, G., Rodriguez-Jimenez, R., Fernández-Caballero, A.: Validation of dynamic virtual faces for facial affect recognition. PLoS ONE (2021)
ElectroCode: Facial expression or emotion recognition android app using TFLite (GPU) and OpenCV. https://www.youtube.com/watch?v=8MblDXgaIzw. Last Accessed 29 Jul 202
Acknowledgements
Grant PID2020-115220RB-C21 funded by MCIN/AEI/10.13039/501100011033 and European funding “ERDF: A way to make Europe”.
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Escobar Blázquez, D., García Jiménez, A.S., Fernández Sotos, P., Fernández Caballero, A., Molina Massó, J.P. (2023). Imitator: A Mobile Application for Rehabilitation of Emotion Recognition. In: Bravo, J., Ochoa, S., Favela, J. (eds) Proceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022). UCAmI 2022. Lecture Notes in Networks and Systems, vol 594. Springer, Cham. https://doi.org/10.1007/978-3-031-21333-5_28
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DOI: https://doi.org/10.1007/978-3-031-21333-5_28
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