Development of a heart rate variability analysis tool

Abstract

Heart Rate Variability (HRV) concerns the analysis of the phenomenon underlying the variability between consecutive heartbeats. During the last three decades, significant effort has been made to understand its physiological basis and implications in different pathologies. Such studies have revealed, among other aspects, that HRV its a mirror of the control actions exerted by the Autonomic Nervous System (ANS) in the Sinoatrial (SA) node. Since the SA node is responsible for setting the heartbeat, the two branches comprising the ANS, sympathetic and parasympathetic, have a special role in controlling such variability. The main goals behind this work were: to develop an open source, reliable and easy-to-use Graphical User Interface (GUI) able to perform a complete HRV analysis; to investigate and possibly implement alternative methods to perform an HRV analysis; and also to validate the developments achieved. As a result of the work carried out, we have manage to develop a cross platform and full featured Python based GUI for HRV computation using the standard procedure based on ECG signals and another alternative methodology based on PPG signals. We have also conducted three different studies in order to analyze the validity of our tool. The first study aimed to validate our HRV GUI and revealed the absence of any significant differences between our GUI and a reference tool. The second study evaluated both specificity and sensitivity of the algorithm that we have developed to detect systolic peaks in PPG signals, where high performance levels were attained. Finally, the third study, aimed to validate the use of PPG signals as an alternative to ECG signals for computing HRV, revealed high levels of correlation between the same parameters computed from ECG and PPG signals acquired simultaneously.