Christov Ivaylo, Raikova Rositsa, Angelova Silvija
Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria.
Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria.
Med Eng Phys. 2018 Jul;57:1-10. doi: 10.1016/j.medengphy.2018.04.007. Epub 2018 Apr 24.
Trunk muscle electromyographic (EMG) signals are often contaminated by the electrical activity of the heart. During low or moderate muscle force, these electrocardiographic (ECG) signals disturb the estimation of muscle activity. Butterworth high-pass filters with cut-off frequency of up to 60 Hz are often used to suppress the ECG signal. Such filters disturb the EMG signal in both frequency and time domain. A new method based on the dynamic application of Savitzky-Golay filter is proposed. EMG signals of three left trunk muscles and pure ECG signal were recorded during different motor tasks. The efficiency of the method was tested and verified both with the experimental EMG signals and with modeled signals obtained by summing the pure ECG signal with EMG signals at different levels of signal-to-noise ratio. The results were compared with those obtained by application of high-pass, 4th order Butterworth filter with cut-off frequency of 30 Hz. The suggested method is separating the EMG signal from the ECG signal without EMG signal distortion across its entire frequency range regardless of amplitudes. Butterworth filter suppresses the signals in the 0-30 Hz range thus preventing the low-frequency analysis of the EMG signal. An additional disadvantage is that it passes high-frequency ECG signal components which is apparent at equal and higher amplitudes of the ECG signal as compared to the EMG signal. The new method was also successfully verified with abnormal ECG signals.
躯干肌肌电图（EMG）信号常被心脏的电活动所干扰。在低或中等肌肉力量时，这些心电图（ECG）信号会干扰肌肉活动的估计。截止频率高达60 Hz的巴特沃斯高通滤波器常被用于抑制ECG信号。此类滤波器会在频域和时域中干扰EMG信号。本文提出了一种基于动态应用Savitzky-Golay滤波器的新方法。在不同运动任务期间记录了三块左躯干肌的EMG信号和纯ECG信号。该方法的有效性通过实验EMG信号以及通过将纯ECG信号与不同信噪比水平的EMG信号相加得到的建模信号进行了测试和验证。将结果与应用截止频率为30 Hz的四阶巴特沃斯高通滤波器所获得的结果进行了比较。所建议的方法能够在整个频率范围内将EMG信号与ECG信号分离，且不会使EMG信号发生幅度失真。巴特沃斯滤波器会抑制0 - 30 Hz范围内的信号，从而无法对EMG信号进行低频分析。另一个缺点是，与EMG信号相比，它会让高频ECG信号成分通过，这在ECG信号幅度相等或更高时很明显。该新方法也成功地通过异常ECG信号得到了验证。
