FastICA peel-off for ECG interference removal from surface EMG.
BACKGROUND
Multi-channel recording of surface electromyographyic (EMG) signals is very likely to be contaminated by electrocardiographic (ECG) interference, specifically when the surface electrode is placed on muscles close to the heart.


METHODS
A novel fast independent component analysis (FastICA) based peel-off method is presented to remove ECG interference contaminating multi-channel surface EMG signals. Although demonstrating spatial variability in waveform shape, the ECG interference in different channels shares the same firing instants. Utilizing the firing information estimated from FastICA, ECG interference can be separated from surface EMG by a "peel off" processing. The performance of the method was quantified with synthetic signals by combining a series of experimentally recorded "clean" surface EMG and "pure" ECG interference.


RESULTS
It was demonstrated that the new method can remove ECG interference efficiently with little distortion to surface EMG amplitude and frequency. The proposed method was also validated using experimental surface EMG signals contaminated by ECG interference.


CONCLUSIONS
The proposed FastICA peel-off method can be used as a new and practical solution to eliminating ECG interference from multichannel EMG recordings.
Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, China.|Guangdong Provincial Work Injury Rehabilitation Center, Guangzhou, China.
Maoqi
M
Chen
Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, China. xuzhang90@ustc.edu.cn.
Xu
X
Zhang
Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, China.
Xiang
X
Chen
The Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Mingxing
M
Zhu
The Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Guanglin
G
Li
Guangdong Provincial Work Injury Rehabilitation Center, Guangzhou, China.|Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center and TIRR Memorial Hermann Research Center, Houston, USA.
Ping
P
Zhou
D000465:Algorithms; D016477:Artifacts; D004562:Electrocardiography; D004576:Electromyography; D008962:Models, Theoretical; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D013499:Surface Properties
ECG interference elimination; Independent component analysis; Multi-channel EMG recording