Off-body Sleep Analysis for Predicting Adverse Behavior in Individuals with Autism Spectrum Disorder

Poor sleep quality in Autism Spectrum Disorder (ASD) individuals is linked to severe daytime behaviors. This study explores the relationship between a prior night's sleep structure and its predictive power for next-day behavior in ASD individuals. The motion was extracted using a low-cost near-...

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Bibliographic Details
Published in:IEEE journal of biomedical and health informatics 2024-11, Vol.PP (11), p.1-10
Main Authors: Kiarashi, Yashar, Suresha, Pradyumna B, Rad, Ali Bahrami, Reyna, Matthew A, Anderson, Conor, Foster, Jenny, Lantz, Johanna, Villavicencio, Tania, Hamlin, Theresa, Clifford, Gari D
Format: Article
Language:English
Subjects:
Accuracy
Autism
Bioinformatics
Biomedical measurement
Cameras
Sensors
Switching circuits
Online Access:Get full text
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Summary:Poor sleep quality in Autism Spectrum Disorder (ASD) individuals is linked to severe daytime behaviors. This study explores the relationship between a prior night's sleep structure and its predictive power for next-day behavior in ASD individuals. The motion was extracted using a low-cost near-infrared camera in a privacy-preserving way. Over two years, we recorded overnight data from 14 individuals, spanning over 2,000 nights, and tracked challenging daytime behaviors, including aggression, self-injury, and disruption. We developed an ensemble machine learning algorithm to predict next-day behavior in the morning and the afternoon. Our findings indicate that sleep quality is a more reliable predictor of morning behavior than afternoon behavior the next day. The proposed model attained an accuracy of 74% and a F1 score of 0.74 in target-sensitive tasks and 67% accuracy and 0.69 F1 score in target-insensitive tasks. For 7 of the 14, betterthan-chance balanced accuracy was obtained (p-value
ISSN:2168-2194
2168-2208
2168-2208
DOI:10.1109/JBHI.2024.3455942