Frasch Martin G, Shen Chao, Wu Hau-Tieng, Mueller Alexander, Neuhaus Emily, Bernier Raphael A, Kamara Dana, Beauchaine Theodore P
Department of Obstetrics and Gynecology, University of Washington, Seattle, WA, USA.
Center on Human Development and Disability, University of Washington, Seattle, WA, USA.
J Autism Dev Disord. 2021 Jan;51(1):346-356. doi: 10.1007/s10803-020-04467-7.
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.
多项研究表明，自闭症谱系障碍（ASD）患者的心率变异性（HRV）存在改变，但这些发现既不具有普遍性，也并非ASD所特有。我们将一组线性和非线性HRV测量方法——包括相位整流信号平均法——应用于从患有ASD的学龄儿童、年龄匹配的发育正常对照儿童以及患有其他以HRV改变为特征的精神疾病（品行障碍、抑郁症）的儿童采集的静息心电图数据片段。我们使用机器学习来识别ASD特有的时间、频率和几何信号分析域（受试者工作特征曲线面积 = 0.89）。这是第一项将患有ASD的儿童与其他以HRV改变为特征的疾病区分开来的研究。尽管样本量小且缺乏外部验证，但研究结果值得开展更大规模的前瞻性研究。
