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使用生理生物信号对患有自闭症谱系障碍的低语言能力青少年近端攻击行为发作进行时间序列预测。

Time-Series Prediction of Proximal Aggression Onset in Minimally-Verbal Youth with Autism Spectrum Disorder Using Physiological Biosignals.

作者信息

Ozdenizci Ozan, Cumpanasoiu Catalina, Mazefsky Carla, Siegel Matthew, Erdoggmus Deniz, Ioannidis Stratis, Goodwin Matthew S

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul;2018:5745-5748. doi: 10.1109/EMBC.2018.8513524.

Abstract

It has been suggested that changes in physiological arousal precede potentially dangerous aggressive behavior in youth with autism spectrum disorder (ASD) who are minimally verbal (MV-ASD). The current work tests this hypothesis through time-series analyses on biosignals acquired prior to proximal aggression onset. We implement ridge-regularized logistic regression models on physiological biosensor data wirelessly recorded from 15 MV-ASD youth over 64 independent naturalistic observations in a hospital inpatient unit. Our results demonstrate proof-of-concept, feasibility, and incipient validity predicting aggression onset 1 minute before it occurs using global, person-dependent, and hybrid classifier models.

摘要

有人提出,在极少言语的自闭症谱系障碍(ASD)青少年(MV-ASD)中,生理唤醒的变化先于潜在危险的攻击性行为。当前的研究通过对近端攻击行为发作前采集的生物信号进行时间序列分析来验证这一假设。我们对从15名MV-ASD青少年在医院住院部进行的64次独立自然观察中无线记录的生理生物传感器数据实施了岭正则化逻辑回归模型。我们的结果证明了概念验证、可行性以及使用全局、个体依赖和混合分类器模型在攻击行为发生前1分钟预测其发作的初步有效性。

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