Consistent assessment of heart rate recovery across exercise intensities

Abstract

Accurate assessment of heart rate (HR) recovery is important for evaluating cardiorespiratory function and endurance capacity. Conventional approaches – such as 1 min or 2 min HR decline exponential fits – often prioritize fitting precision, yet can show substantial variability across individuals and exercise intensities, limiting their broader applicability. In this study, we examined a Decay Time Constant (Decay TC) derived from a first-order differential model applied to HR data scaled between exercise termination and 2 min post-exercise. Thirty-five healthy adults performed robot-resisted knee-up exercises at three intensities (72, 84, and 96 RPM), with HR continuously monitored via a wireless chest sensor. Normalization based on the first-order model reduced the influence of differing starting HR values and recovery slopes, enabling the Decay TC to reflect recovery characteristics that remained relatively consistent across intensities. Correlation analysis – performed overall and by sex and age group – showed that this Decay TC maintained more stable relationships with submaximal VO₂max than conventional HR recovery indicators, with moderate-to-strong correlations ($\left|R\right|$ up to 0.93). Multivariable regression confirmed it as a significant predictor, but the aim was not to maximize VO₂max prediction accuracy or optimize curve-fitting, but rather to provide a simple, interpretable measure that captures an individual’s consistent recovery profile as a potential physiological signature. These findings suggest that the Decay TC obtained from scaled HR data offers a practical metric for characterizing HR recovery dynamics, with potential for integration into endurance assessment protocols and wearable health monitoring systems.