On the Autonomic Control of Heart Rate Variability: How the Mean Heart Rate Affects Spectral and Complexity Analysis and a Way to Mitigate its Influence (Real data)

Heart Rate Variability (HRV) analysis allows for assessing autonomic control from the beat-by-beat dynamics of the time series of cardiac intervals. However, some HRV indices may strongly correlate with the mean heart rate, possibly flawing the interpretation of HRV changes in terms of autonomic control. Therefore, this study (published on "Mathematics" 2025) aims at 1) investigating how HRV indices of fluctuations amplitude and multiscale complex dynamics of cardiac time series faithfully describe the autonomic control at different heart rates through a mathematical model of the generation of cardiac action potentials driven by realistically synthesized autonomic modulations; 2) proposing an alternative procedure of HRV analysis less sensitive to the mean heart rate. Application of our procedure to real cardiac intervals recorded in different postures suggests that the dependency of these indices on the heart rate may importantly affect the physiological interpretation of HRV. By contrast, multiscale complexity indices do not substantially depend on the heart rate provided that multiscale analyses are defined on a time- rather than a beat- basis. The datasets available on this repository are the real data (Matlab format) collected in volunteers.