Indirect respiratory monitoring via single-lead wearable ECG: influence of motion artifacts and devices on respiratory rate estimations

Among all the vital signs, respiratory rate (RR) has been demonstrated to be predictive of early health issues and an accurate marker for evaluating treatment efficacy and tracking disease progression. RR monitoring during sleep may be crucial to identify breathing pattern alterations common in sleep apnea, COPD, heart failure, and diabetes patients.Several technologies have been explored to continuously estimate respiratory and cardiac biomarkers during sleep without sacrificing patient comfort. Electrocardiographic signals (ECG) can be used to extract respiratory patterns indirectly. However, the quality of ECG significantly impacts the derived respiratory signal and estimated RR values. Wearable single-lead ECG devices may face challenges like low signal-to-noise ratio and motion artifacts, mainly caused by the user's natural movement during sleep and inadequate adherence between the skin and electrodes.This preliminary study evaluates the performance of three single-lead ECG wearable devices (a chest strap, a thoracic belt, and a patch) in providing RR values from ECG-derived respiration (EDR) during sleep over two nights in a home setting. The quality of the signal and motion artifacts have been investigated as influencing factors in the RR estimations. Two commonly used EDR methods have been tested.Results show better performance of the ECG thoracic belt in providing reliable ECG signal over the night and robust estimation of RR values, with mean absolute error and mean absolute percentage error always lower than 0.7 breaths/min and 6.4%.