Empirical mode decomposition as a tool to remove the function electrical stimulation artifact from surface electromyograms: preliminary investigation.
Rectification of surface EMGs during electrical stimulations (ES) is still a problem to be solved. The broad band frequency components of ES artifact overlap with the EMG spectrum, make this task challenging. In this study, we investigate the potential use of empirical mode decomposition (EMD) method to remove the stimulus artifact from surface EMGs collected during such applications. We hypothesize that the EMD algorithm provides a suitable platform for decomposing the EMG signal into physically meaningful intrinsic modes which can be used to isolate ES artifact. Basic EMD is tested on two signals - ES induced EMG and EMG of voluntary contractions added with simulated ES signal. The algorithm isolates the EMG from ES artifact with considerable success. Further, the EMD method along with the energy operator -TKEO gives even better representation of the EMG signal. However, some high frequency data was lost during reconstruction process. Hence, there is further need to investigate the relationship between the EMD parameters and stimulus artifact properties so that the algorithm can be optimized to reconstruct pure artifact free EMG signal with minimum lost of data.
Kessler Foundation, West Orange, NJ 07052, USA. rpilkar@kesslerfoundation.org
Rakesh B
RB
Pilkar
Mathew
M
Yarossi
Gail
G
Forrest
D000328:Adult; D000465:Algorithms; D016477:Artifacts; D004558:Electric Stimulation; D004576:Electromyography; D005583:Fourier Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D009119:Muscle Contraction / Q000502:physiology; D018482:Muscle, Skeletal / Q000502:physiology; D012815:Signal Processing, Computer-Assisted; D013499:Surface Properties