Literature DB >> 30441641

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

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

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.

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Year:  2018        PMID: 30441641     DOI: 10.1109/EMBC.2018.8513524

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  2 in total

1.  Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction.

Authors:  Mo Han; Özan Ozdenizci; Ye Wang; Toshiaki Koike-Akino; Deniz Erdoğmuş
Journal:  IEEE Signal Process Lett       Date:  2020-08-31       Impact factor: 3.109

2.  Multi-level modeling with nonlinear movement metrics to classify self-injurious behaviors in autism spectrum disorder.

Authors:  Kristine D Cantin-Garside; Divya Srinivasan; Shyam Ranganathan; Susan W White; Maury A Nussbaum
Journal:  Sci Rep       Date:  2020-10-07       Impact factor: 4.379

  2 in total

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