| Literature DB >> 32449059 |
Martin G Frasch1,2, Chao Shen3, Hau-Tieng Wu3,4, Alexander Mueller5, Emily Neuhaus6,7, Raphael A Bernier8, Dana Kamara9, Theodore P Beauchaine9.
Abstract
Several studies show altered heart rate variability (HRV) in autism spectrum disorder (ASD), but findings are neither universal nor specific to ASD. We apply a set of linear and nonlinear HRV measures-including phase rectified signal averaging-to segments of resting ECG data collected from school-age children with ASD, age-matched typically developing controls, and children with other psychiatric conditions characterized by altered HRV (conduct disorder, depression). We use machine learning to identify time, frequency, and geometric signal-analytical domains that are specific to ASD (receiver operating curve area = 0.89). This is the first study to differentiate children with ASD from other disorders characterized by altered HRV. Despite a small cohort and lack of external validation, results warrant larger prospective studies.Entities:
Keywords: Biomarker; Electrocardiogram; Heart rate variability
Mesh:
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Year: 2021 PMID: 32449059 DOI: 10.1007/s10803-020-04467-7
Source DB: PubMed Journal: J Autism Dev Disord ISSN: 0162-3257