A wavelet-based adaptive filter for removing ECG interference in EMGdi signals
被引:37
作者:
Zhan, Choujun
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机构:
City Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R ChinaCity Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China
Zhan, Choujun
[1
]
Yeung, Lam Fat
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机构:
City Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R ChinaCity Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China
Yeung, Lam Fat
[1
]
Yang, Zhi
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机构:
Sun Yat Sen Univ, Dept Elect & Commun Engn, Sch Informat Sci & Technol, Guangzhou 510275, Guangdong, Peoples R ChinaCity Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China
Yang, Zhi
[2
]
机构:
[1] City Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China
[2] Sun Yat Sen Univ, Dept Elect & Commun Engn, Sch Informat Sci & Technol, Guangzhou 510275, Guangdong, Peoples R China
Diaphragmatic electromyogram (EMGdi) signals convey important information on respiratory diseases. In this paper, an adaptive filter for removing the electrocardiographic (ECG) interference in EMGdi signals based on wavelet theory is proposed. Power spectrum analysis was performed to evaluate the proposed method. Simulation results show that the power spectral density (PSD) of the extracted EMGdi signal from an ECG corrupted signal is within 1.92% average error relative to the original EMGdi signal. Testing on clinical EMGdi data confirm that this method is also efficient in removing ECG artifacts from the corrupted clinical EMGdi signal. Crown Copyright (C) 2009 Published by Elsevier Ltd. All rights reserved.