Abstract
Respiratory sinus arrhythmia (RSA) is a quantitative metric that reflects autonomic nervous system regulation and provides a physiological marker of attentional engagement that supports cognitive and affective regulatory processes. RSA can be added to executive function (EF) assessments with minimal participant burden because of the commercial availability of lightweight, wearable electrocardiogram (ECG) sensors. However, the inclusion of RSA data in large data collection efforts has been hindered by the time-intensive processing of RSA. In this study we evaluated the performance of an automated RSA-scoring method in the context of an EF study in preschool-aged children. The absolute differences in RSA across both scoring methods were small (mean RSA differences = -0.02-0.10), with little to no evidence of bias for the automated relative to the hand-scoring approach. Moreover, the relative rank-ordering of RSA across both scoring methods was strong (rs = .96-.99). Reliable changes in RSA from baseline to the EF task were highly similar across both scoring methods (96%-100% absolute agreement; Kappa = .83-1.0). On the basis of these findings, the automated RSA algorithm appears to be a suitable substitute for hand-scoring in the context of EF assessment.