Title :
Nonstationary Harmonic Modeling for ECG Removal in Surface EMG Signals
Author :
Zivanovic, Miroslav ; Gonzalez-Izal, M.
Author_Institution :
Electr. Eng. Dept., Public Univ. of Navarra, Pamplona, Spain
fDate :
6/1/2012 12:00:00 AM
Abstract :
We present a compact approach for mitigating the presence of electrocardiograms (ECG) in surface electromyographic (EMG) signals by means of time-variant harmonic modeling of the cardiac artifact. Heart rate and QRS complex variability, which often account for amplitude and frequency time variations of the ECG, are simultaneously captured by a set of third-order constant-coefficient polynomials modulating a stationary harmonic basis in the analysis window. Such a characterization allows us to significantly suppress ECG from the mixture by preserving most of the EMG signal content at low frequencies (less than 20 Hz). Moreover, the resulting model is linear in parameters and the least-squares solution to the corresponding linear system of equations efficiently provides model parameter estimates. The comparative results suggest that the proposed method outperforms two reference methods in terms of the EMG preservation at low frequencies.
Keywords :
electrocardiography; electromyography; least squares approximations; medical signal processing; signal denoising; ECG amplitude variations; ECG frequency time variations; ECG removal; ECG signal suppression; QRS complex variability; cardiac artifact time variant harmonic modeling; electrocardiograms; heart rate variability; least squares solution; nonstationary harmonic modeling; parameter estimates; surface EMG signals; surface electromyographic signals; third order constant coefficient polynomials; Electrocardiography; Electromyography; Frequency modulation; Harmonic analysis; Power harmonic filters; Signal to noise ratio; Time frequency analysis; Electrocardiogram (ECG) suppression; harmonic modeling; nonnonstationary signals; surface electromyography; Algorithms; Artifacts; Computer Simulation; Diagnosis, Computer-Assisted; Electrocardiography; Electromyography; Humans; Models, Statistical; Reproducibility of Results; Sensitivity and Specificity;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2012.2191287