Comparative analysis of methods for calculating HRV values on heart rate monitoring devices

The aim of the study is to conduct a comparative analysis of HRV calculation methods and how they affect its measures (SDNN, SDNN Index, SDANN, RSA Index, Mean RR, RMSSD, pNN50) and their quality. Modern medical devices offer many possibilities, including heart rate and ECG measurement. An important issue in assessing heart function is HRV and its measures, which allow us to determine how the heart responds to different conditions, but the question of how to measure HRV and how its calculation works in different conditions remains open. The paper will show how HRV changes depending on frequency during rest, activity (walking), and sleep. HRV will be calculated using both an analytical method (using the Pan-Tompkins and U-Net algorithms) and a convolutional neural network.