Respiratory Signals Derived from Electromyograms in Single-Lead Electrocardiograms

Abstract

Wearable devices demand convenient respiration measurements for the diagnosis and monitoring of respiratory disorders. We proposed a method to derive respiratory signals from electromyograms (EMG) in single-lead electrocardiograms. Compared with the traditional filter- and feature-based methods to derive respiratory signals from cardiac activities, the proposed method is free from the influence of cardiac arrhythmias and baseline wandering. Based on experiments of 12 subjects using Holter ECG leads, the proposed method demonstrated an average sensitivity 93.3% and an average positive predictive value 91.3% for the detection of respiration. This method is especially useful in wearable devices to monitor respiration, and requires no supplementary electrodes or hardware modifications.