Estimation of heart rate variability from peripheral pulse wave using PPG sensor

Abstract

Heart rate variability (HRV) analysis is gaining acceptance as a potential non-invasive means of cardiac assessment in clinical as well as research domains. Although it is a standard practice to derive HRV from the R-R peaks of electrocardiogram (ECG), there have been attempts to deduce it from peripheral pulse wave signal. HRV is measured using photoplethysmographic (PPG) pulse wave signal in this work. A versatile algorithm governed by the physiology of the cardiovascular system developed by the authors is used to derive peak intervals from the PPG signal. In addition to normal time and frequency domain techniques, sequential trend analysis (STA) is applied to analyse HRV. Out of 20 subjects monitored, the results of three, one healthy and two with known cardiac problems, are presented and discussed. In all cases monitored, the results of HRV deduced from PPG are in tune with clinical picture of the subjects. The usefulness of STA in the analysis of HRV is also discussed.