Adaptive Noise-Reduction Algorithm for Diaphragm Electromyography Based on Linear Prediction

Abstract

Diaphragm electromyography (EMGdi) collected by esophageal electrodes can provide important information for the assessment of the respiratory system. But it is vulnerable to electrocardiogram (ECG) interference. It is pointed out that the autocorrelation function of EMGdi is significantly different from that of ECG. And accordingly, a filter based on linear prediction is proposed to suppress the ECG interference. The coefficients of the filter are adjusted on line so as to adapt to different subjects or the slow change of the autocorrelation function of the same subject over time. The filter is applied to clinically acquired signals, and the results demonstrate that it can effectively suppress the ECG interference, and the filtered EMGdi is in a good synchronization with the transdiaphragmatic pressure (Pdi).