Heart Rate Variability Estimation in Electrocardiogram Signals Interferences Based on Photoplethysmography Signals

Abstract

In order to improve the accuracy and real-timelines of heart rate variability (HRV) estimation in electrocardiogram (ECG) signals interferences, a novel HRV estimation method based on photoplethysmography (PPG) signals is proposed. The short-time autocorrelation principle is used to detect interferences in ECG signals, then, the improving sliding window iterative Discrete Fourier Transform (DFT) is used to estimate HRV in ECG interferences from the synchronously acquisitioned PPG signals. The international commonly used MIT-BIT Arrhythmia Database/Challenge 2014 Training Set is used to verify the interferences detection algorithm and HRV estimation algorithm which are proposed. At the same time, the proposed algorithms are compared with recently existing representative interferences detection algorithm based on RR intervals and PRV directly replaced HRV algorithm, respectively. The results show that the proposed methods are more accurate and more real-time.