Bell, Maria;
Robinson, Elise;
Day, Sally;
Gilbert, Thomas Jamin;
Hamilton, Antonia F De C;
Ward, Jamie A;
(2022)
Lessons on Collecting Data from Autistic Children using Wrist-worn Sensors.
Proceedings of the 2022 ACM International Symposium on Wearable Computers
pp. 6-10.
10.1145/3544794.3558478.
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Abstract
Autism is a diverse neurodevelopmental condition that has a hugely varying impact of the lives of autistic people. It is only in the last decades that a greater understanding and public awareness of the autism spectrum has come about, in-part thanks to a growing body of research into the condition. Wearable technology offers great promise in furthering autism research by providing an ability to do detailed behavioral analysis in real-life settings, such as in schools, with minimal intrusion. Such work is particularly crucial in exploring behaviours of those with complex needs and intellectual disabilities, a group who traditionally have been under-served. To achieve this there is a need for wearables that are both practical and acceptable to the individuals being studied. This paper presents our findings from a human-centred design approach to developing and deploying wrist-worn sensors among a diverse population of 16 autistic and 12 neurotypical children over a period of several months. Findings and recommendations from this work highlight the need to take both sensory factors and emotional dysregulation into account when designing wearables for autism. Individual aesthetic and social considerations are particularly important for older children. Equally, a period of sensor desensitisation is necessary when working among those with more complex needs.
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