Recent advances in wearable sensing technology have enabled simultaneous measurement of heart activity and body movement using devices equipped with both ECG recording and 3-axis accelerometers. This study examined whether transient heart rate (HR) responses to physical activity can be accurately characterized under free-living conditions. Continuous RR interval data and activity levels derived from accelerometer signals were analyzed using a multivariate autoregressive (MVAR) model. Results from 12 male participants showed a strong correlation between predicted and observed HR responses (r2 = 0.93, r = 0.96, p < 0.001). These findings indicate that up to 93% of transient HR dynamics associated with daily physical activity can be explained by the model. While these results are preliminary due to the limited sample size, the approach provides a promising framework for the noninvasive, continuous monitoring of cardiovascular responses in everyday health and wellness applications.
Yuda et al. (2025) studied this question.