Feasibility of Wearable Armband Bipolar ECG Lead-1 for Long-term HRV Monitoring by Combined Signal Averaging and 2-stage Wavelet Denoising

Abstract

Heart rate variability (HRV) is a clinically important and prominent cardiovascular diseases diagnostic factor. Since HRV is a highly individualised measure, long-term continuous ECG and HRV tracking using a non-invasive armband-based wearable monitoring device is an appealing option for HRV trend-based indicator of general health. Therefore, we investigated the correlation between the bipolar arm-ECG Lead-1 (electrodes axis coplanar to chest and at axilla level) HRV measurements and their corresponding standard measurements from the standard chest ECG Lead I, using a 2 stage dB4 Wavelet-based denoising process supported by an iterative signal-averaged ECG optimal-thresholding adaptation algorithm on the arm-ECG signal, followed by a Pan-Tompkins QRS-detection algorithm. The conventional Pearson correlation coefficient was used as the main performance assessment metric. Four clinically common HRV time-domain metrics were studied: SDNN, RR-rms, RR-median and the interquartile-range value of normal-to-normal heartbeat intervals (IQRNN). The results revealed that RR-rms and RR-median HRV metrics from bipolar arm-ECG (Lead-1) closely correlated to the values measured from the standard Lead-I and present potential for clinical use.