Before revision:  11 years) with (n=18) and without ASD (n=18), we tested a set of  linear and nonlinear HRV measures, including phase rectified signal averaging (PRSA) , applied to a segment of ECG collected under resting conditions for their predictive properties of ASD . We identified HRV measures derived from time, frequency  and geometric signal-analytical domains which are changed in ASD children relative to peers without ASD and correlate to psychometric scores (p<0.05 for each) .
After revision:  11 years) with (n=18) and without ASD (n=18), we tested a set of linear and nonlinear HRV measures, including phase rectified signal averaging (PRSA) , applied to a segment of resting ECG, for associations with ASD vs. other psychiatric conditions. Using machine learning, we identify HRV measures derived from time, frequency and geometric signal-analytical domains which are changed in ASD children relative to peers without ASD and correlate to psychometric scores (p<0.05 for each) .