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Open AccessProceedings

A Study on the Perceptions of Autistic Adolescents towards Mainstream Emotion Recognition Technologies

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BSS Telemedicine Group, Creative Technology, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, 7522 NB Enschede, The Netherlands
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Department of Computer Architecture & Computer Technology, University of Granada, E-18071 Granada, Spain
*
Author to whom correspondence should be addressed.
Presented at the 12th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2018), Punta Cana, Dominican Republic, 4–7 December 2018.
Proceedings 2018, 2(19), 1200; https://doi.org/10.3390/proceedings2191200
Published: 23 October 2018
(This article belongs to the Proceedings of UCAmI 2018)
Autistic people have difficulties in recognizing and expressing emotions from/to other people. Technologies can help to facilitate the communication and understanding between autistic and other people. This work particularly investigates the requirements autistic adolescents have on technologies that can measure bodily responses to recognize their emotions. A smartwatch, smart-patch and infrared camera were evaluated as potential everyday use devices to measure emotion. User requirements on emotion recognition technologies were elicited through an online survey (73 completed responses) and ten semi-structured interviews with autistic adolescents. The smartwatch is the preferred product, followed by the smart-patch. Infrared cameras are deemed unsuitable devices.
Keywords: autism; emotion recognition technology; smartwatch; smart-patch; infrared camera; human computer interaction (HCI); usability testing; sensor applications and deployments autism; emotion recognition technology; smartwatch; smart-patch; infrared camera; human computer interaction (HCI); usability testing; sensor applications and deployments
MDPI and ACS Style

Nijeweme-d’Hollosy, W.O.; Notenboom, T.; Banos, O. A Study on the Perceptions of Autistic Adolescents towards Mainstream Emotion Recognition Technologies. Proceedings 2018, 2, 1200.

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