@article{ref1,
title="Predicting imminent aggression onset in minimally-verbal youth with autism spectrum disorder using preceding physiological signals",
journal="International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]",
year="2018",
author="Goodwin, Matthew S. and Özdenizci, Ozan and Cumpanasoiu, Catalina and Tian, Peng and Guo, Yuan and Stedman, Amy and Peura, Christine and Mazefsky, Carla and Siegel, Matthew and Erdoğmuş, Deniz and Ioannidis, Stratis",
volume="2018",
number="",
pages="201-207",
abstract="We test the hypothesis that changes in preceding physiological arousal can be used to predict imminent aggression proximally before it occurs in youth with autism spectrum disorder (ASD) who are minimally verbal (MV-ASD). We evaluate this hypothesis through statistical analyses performed on physiological biosensor data wirelessly recorded from 20 MV-ASD youth over 69 independent naturalistic observations in a hospital inpatient unit. Using ridge-regularized logistic regression, results demonstrate that, on average, our models are able to predict the onset of aggression 1 minute before it occurs using 3 minutes of prior data with a 0.71 AUC for global, and a 0.84 AUC for person-dependent models.<p /> <p>Language: en</p>",
language="en",
issn="2153-1633",
doi="10.1145/3240925.3240980",
url="http://dx.doi.org/10.1145/3240925.3240980"
}