Open AccessA DENOISING METHOD OF DIAPHRAGM ELECTROMYOGRAM SIGNALS BASED ON DUAL-THRESHOLD FILTER
Author(s) -
Shuang-Miao Li,
ZHIWEI LI,
JIANHENG ZHANG,
HAN ZHANG
Publication year - 2022
Publication title -
journal of mechanics in medicine and biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.236
H-Index - 30
eISSN - 1793-6810
pISSN - 0219-5194
DOI - 10.1142/s0219519422400097
Subject(s) - noise reduction , computer science , filter (signal processing) , signal (programming language) , artificial intelligence , pattern recognition (psychology) , wavelet , qrs complex , diaphragm (acoustics) , speech recognition , computer vision , vibration , acoustics , medicine , cardiology , physics , programming language
Diaphragmatic electromyography (EMGdi) signals can effectively reflect human respiratory process and effort, but simultaneously interfered by electrocardiogram (ECG) signals, leading to the limited application of EMGdi signals. Conventional denoising schemes for ECG cancellation from EMGdi signals are usually limited to the cases of irregular ECG signals. For this purpose, this paper proposes a denoising method of ECG signals by using a dual-threshold filter, which performs effectively in the scenarios of irregular ECG condition, such as arrhythmia. Specifically, we first employ wavelet transform to decompose EMGdi signals to wavelets of different frequencies, by which QRS complex detection is performed to determine the location of ECG signals. Then we propose to remove the ECG interference by reforming the interference range with the adjacent signals. Experimental results indicate that the proposed denoising method performs superior to the state-of-the-art schemes, especially for the cases of weak EMGdi signal scenarios.