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Adaptive cancellation of ECG artifacts in the diaphragm electromyographic signals obtained through intraoesophageal electrodes during swallowing and inspiration
Author(s) -
CHEN J. D. Z.,
LIN Z. Y.,
RAMAHI M.,
MITTAL R. K.
Publication year - 1994
Publication title -
neurogastroenterology and motility
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.489
H-Index - 105
eISSN - 1365-2982
pISSN - 1350-1925
DOI - 10.1111/j.1365-2982.1994.tb00194.x
Subject(s) - signal (programming language) , artifact (error) , adaptive filter , computer science , filter (signal processing) , electromyography , speech recognition , pattern recognition (psychology) , diaphragm (acoustics) , artificial intelligence , computer vision , algorithm , vibration , acoustics , medicine , physical medicine and rehabilitation , programming language , physics
This paper presents a new and effective adaptive filtering method for the cancellation of electrocardiogram (ECG) artifacts in the electromyographic (EMG) signals obtained through intraoesophageal electrodes. This technique requires adjustable filter weights and two input signals. The primary input signal was the EMG signal containing the ECG artifact and the reference or the second input was the ECG signal measured simultaneously by two chest electrodes. The adaptive filter weights were initially set at zero and iteratively adjusted according to a least mean square algorithm proposed in this paper. The filter weights were adjusted in such a way that the output of the adaptive filter was a replica of the contaminating ECG signal, which was then subtracted from the EMG signal, yielding an ECG‐free EMG signal. The performance of the proposed method was investigated using computer simulations. It was found that ECG artifacts could be effectively cancelled while the EMG signal was not affected by adaptive filtering. Its applications showed that the proposed new algorithm had better performance than the conventional least mean square algorithm. The EMG signals were obtained in six healthy subjects, during swallows (oesophageal muscle EMG) and deep inspiration (crural diaphragm EMG). Our results demonstrated the effective cancellation of the ECG artifact in both swallow‐induced and inspiration‐related EMG signals. Spectral analysis of the EMG was performed on the ECG‐free EMG signal. The inspiration‐related EMG signal was found to have higher frequency components than the swallow‐related EMG.