Estimation of beat-to-beat interval from wearable photoplethysmography sensor on different measurement sites during daily activities

Abstract

In this study, we present an algorithm to detect beat-to-beat interval from PPG in the presence of motion artifacts. Our approach includes splitting slowly varying DC components, statistical detrending, and Bessel filtering and Fast Fourier Transform with square window to reduce motion artifacts dependent on spectrum analysis. The algorithm segments beat intervals with a spectrogram to find the characteristic points of the waveform such as systolic and diastolic points. Interbeat intervals (IBI) are determined from these characteristic points to calculate heart rate. The PPG IBI algorithm is validated against ECG RR intervals from five different measurement sites during three daily activities. The results show that the most accurate IBI and HR detection from a wearable PPG device during regular user activity is from the upper arm or finger.