Chen Maoqi, Zhang Xu, Chen Xiang, Zhu Mingxing, Li Guanglin, Zhou Ping
Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, China.
Guangdong Provincial Work Injury Rehabilitation Center, Guangzhou, China.
Biomed Eng Online. 2016 Jun 13;15(1):65. doi: 10.1186/s12938-016-0196-8.
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.
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.
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.
The proposed FastICA peel-off method can be used as a new and practical solution to eliminating ECG interference from multichannel EMG recordings.
表面肌电图（EMG）信号的多通道记录很可能受到心电图（ECG）干扰的污染，尤其是当表面电极放置在靠近心脏的肌肉上时。
提出了一种基于快速独立成分分析（FastICA）的新型剥离方法，以去除污染多通道表面EMG信号的ECG干扰。尽管不同通道中的ECG干扰在波形形状上表现出空间变异性，但其放电瞬间是相同的。利用从FastICA估计的放电信息，通过“剥离”处理可将ECG干扰与表面EMG分离。通过结合一系列实验记录的“干净”表面EMG和“纯”ECG干扰，用合成信号对该方法的性能进行了量化。
结果表明，新方法能够有效去除ECG干扰，对表面EMG的幅度和频率几乎没有失真。所提出的方法也通过受ECG干扰污染的实验表面EMG信号进行了验证。
所提出的FastICA剥离方法可作为一种新的实用解决方案，用于消除多通道EMG记录中的ECG干扰。
