The age distribution should be considered when choosing robust HRV parameters

Heart rate variability (HRV) is a marker for autonomic regulation. Its estimation is influenced by measurement errors in heartbeat intervals and the robustness of each HRV parameter is thought to also depend on its population baseline value. To investigate this dependence, we use Monte Carlo Simulation to introduce artificial errors in heartbeat interval data sampled from different age groups. Thereby, we show that using certain HRV parameters that are easily influenced by errors in heartbeat intervals should be avoided for older age groups.