title: A wavelet-based adaptive filter for removing ECG interference in EMGdi signals.
abstract: 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.
authors.affiliation: Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China. zchoujun2@student.cityu.edu.hk
authors.forename: Choujun
authors.initials: C
authors.lastname: Zhan
authors.forename: Lam Fat
authors.initials: LF
authors.lastname: Yeung
authors.forename: Zhi
authors.initials: Z
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D004576:Electromyography / Q000379:methods*; D006801:Humans; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted