AI Article Synopsis
- Several studies indicate changes in heart rate variability (HRV) in autism spectrum disorder (ASD), but results vary and aren't exclusive to ASD.
- The researchers analyzed resting ECG data from children with ASD, typically developing peers, and those with other psychiatric issues to distinguish HRV patterns.
- Using machine learning, they achieved a high accuracy in identifying HRV characteristics unique to ASD, highlighting the need for larger studies despite the current limitations of their small sample size.
Article 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.
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| http://dx.doi.org/10.1007/s10803-020-04467-7 | DOI Listing |
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