Social robots and wearable sensors for mitigating meltdowns in autism - A pilot test

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Abstract

Young individuals with ASD may exhibit challenging behaviors. Among these, self-injurious behavior (SIB) is the most devastating for a person’s physical health and inclusion within the community. SIB refers to a class of behaviors that an individual inflicts upon himself or herself, which may potentially result in physical injury (e.g. hitting one’s own head with the hand or the wrist, banging one’s head on the wall, biting oneself and pulling out one’s own hair). We evaluate the feasibility of a wrist-wearable sensor in detecting challenging behaviors in a child with autism prior to any visible signs through the monitoring of the child’s heart rate, electrodermal activity, and movements. Furthermore, we evaluate the feasibility of such sensor to be used on an ankle instead of the wrist to reduce harm due to hitting oneself by hands and to improve wearable tolerance. Thus, we conducted two pilot tests. The first test involved a wearable sensor on the wrist of a child with autism. In a second test, we investigated wearable sensors on the wrist and on the ankle of a neurotypical child. Both pilot test results showed that the readings from the wearable sensors correlated with the children’s behaviors that were obtained from the videos taken during the tests. Wearable sensors could provide additional information that can be passed to social robots or to the caregivers for mitigating SIBs.

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Cabibihan, J. J., Chellali, R., So, C. W. C., Aldosari, M., Connor, O., Alhaddad, A. Y., & Javed, H. (2018). Social robots and wearable sensors for mitigating meltdowns in autism - A pilot test. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11357 LNAI, pp. 103–114). Springer Verlag. https://doi.org/10.1007/978-3-030-05204-1_11

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