Abstract

Diaphragmatic Electromyography(EMGdi), a biomedical signal produced by diaphragm tissue in the process of respiration, has become an important part in diagnosis of respiratory diseases. As diaphragm is close to the heart, Electrocardiogram(ECG) is the strongest interference in the collection of EMGdi. Before removing ECG noise, locating the interference interval of ECG is an essential prerequisite step. In order to obtain low frequency coefficients, stationary wavelet transform(SWT) is used for decomposing raw EMGdi. In order to enlarge the difference between EMGdi and ECG signal, with the help of the Wing function, low frequency coefficients are applied for constructing the module of ECG. If the sliding filter result of module of ECG is higher than that of raw EMGdi, these intervals can be regarded as the ECG interference. According to the Donoho wavelet hard threshold equation, each threshold of ECG interference is calculated by those coefficients starting from the its previous ECG interference to its next ECG interference. Those coefficients located in ECG interference interval are processed by inverse hard threshold. Finally, the de-noising EMGdi can be reconstructed by inverse stationary wavelet transform with processed coefficients in interference interval and untreated coefficients in non-disturbing section. De-noising results of two cases of clinical EMGdi show that the algorithm developed in this paper can cancel the ECG interference in EMGdi availably and locate ECG interference effectively.

Full Text
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