Journal
JOURNAL OF AUTISM AND DEVELOPMENTAL DISORDERS
Volume 51, Issue 1, Pages 346-356Publisher
SPRINGER/PLENUM PUBLISHERS
DOI: 10.1007/s10803-020-04467-7
Keywords
Heart rate variability; Electrocardiogram; Biomarker
Categories
Funding
- CIHR
- FRQS
- Sloan
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The study examines altered heart rate variability (HRV) in children with autism spectrum disorder (ASD) compared to typically developing children and those with other psychiatric conditions. Using machine learning, specific time, frequency, and geometric signal-analytical domains for ASD were identified. Despite a small cohort and lack of external validation, results suggest the need for larger prospective studies to validate findings.
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.
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