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Predicting aggression to others in youth with autism using a wearable biosensor
Author(s) -
Goodwin Matthew S.,
Mazefsky Carla A.,
Ioannidis Stratis,
Erdogmus Deniz,
Siegel Matthew
Publication year - 2019
Publication title -
autism research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.656
H-Index - 66
eISSN - 1939-3806
pISSN - 1939-3792
DOI - 10.1002/aur.2151
Subject(s) - autism spectrum disorder , aggression , autism , psychology , wearable computer , clinical psychology , developmental psychology , computer science , embedded system
Unpredictable and potentially dangerous aggressive behavior by youth with Autism Spectrum Disorder (ASD) can isolate them from foundational educational, social, and familial activities, thereby markedly exacerbating morbidity and costs associated with ASD. This study investigates whether preceding physiological and motion data measured by a wrist‐worn biosensor can predict aggression to others by youth with ASD. We recorded peripheral physiological (cardiovascular and electrodermal activity) and motion (accelerometry) signals from a biosensor worn by 20 youth with ASD (ages 6–17 years, 75% male, 85% minimally verbal) during 69 independent naturalistic observation sessions with concurrent behavioral coding in a specialized inpatient psychiatry unit. We developed prediction models based on ridge‐regularized logistic regression. Our results suggest that aggression to others can be predicted 1 min before it occurs using 3 min of prior biosensor data with an average area under the curve of 0.71 for a global model and 0.84 for person‐dependent models. The biosensor was well tolerated, we obtained useable data in all cases, and no users withdrew from the study. Relatively high predictive accuracy was achieved using antecedent physiological and motion data. Larger trials are needed to further establish an ideal ratio of measurement density to predictive accuracy and reliability. These findings lay the groundwork for the future development of precursor behavior analysis and just‐in‐time adaptive intervention systems to prevent or mitigate the emergence, occurrence, and impact of aggression in ASD. Autism Res 2019, 12: 1286–1296 . © 2019 International Society for Autism Research, Wiley Periodicals, Inc. Lay Summary Unpredictable aggression can create a barrier to accessing community, therapeutic, medical, and educational services. The present study evaluated whether data from a wearable biosensor can be used to predict aggression to others by youth with autism spectrum disorder (ASD). Results demonstrate that aggression to others can be predicted 1 min before it occurs with high accuracy, laying the groundwork for the future development of preemptive behavioral interventions and just‐in‐time adaptive intervention systems to prevent or mitigate the emergence, occurrence, and impact of aggression to others in ASD.