Department of Electrical and Electronic Engineering, Public University of Navarra, 31006, Navarra, Spain.
Med Biol Eng Comput. 2018 Aug;56(8):1391-1402. doi: 10.1007/s11517-017-1773-0. Epub 2018 Jan 11.
Scanning-EMG is an electrophysiological technique in which the electrical activity of the motor unit is recorded at multiple points along a corridor crossing the motor unit territory. Correct analysis of the scanning-EMG signal requires prior elimination of interference from nearby motor units. Although the traditional processing based on the median filtering is effective in removing such interference, it distorts the physiological waveform of the scanning-EMG signal. In this study, we describe a new scanning-EMG signal processing algorithm that preserves the physiological signal waveform while effectively removing interference from other motor units. To obtain a cleaned-up version of the scanning signal, the masked least-squares smoothing (MLSS) algorithm recalculates and replaces each sample value of the signal using a least-squares smoothing in the spatial dimension, taking into account the information of only those samples that are not contaminated with activity of other motor units. The performance of the new algorithm with simulated scanning-EMG signals is studied and compared with the performance of the median algorithm and tested with real scanning signals. Results show that the MLSS algorithm distorts the waveform of the scanning-EMG signal much less than the median algorithm (approximately 3.5 dB gain), being at the same time very effective at removing interference components. Graphical Abstract The raw scanning-EMG signal (left figure) is processed by the MLSS algorithm in order to remove the artifact interference. Firstly, artifacts are detected from the raw signal, obtaining a validity mask (central figure) that determines the samples that have been contaminated by artifacts. Secondly, a least-squares smoothing procedure in the spatial dimension is applied to the raw signal using the not contaminated samples according to the validity mask. The resulting MLSS-processed scanning-EMG signal (right figure) is clean of artifact interference.
扫描肌电图是一种电生理学技术，其中沿穿过运动单位区域的走廊在多个点记录运动单位的电活动。正确分析扫描肌电图信号需要预先消除来自附近运动单位的干扰。虽然基于中值滤波的传统处理在消除这种干扰方面非常有效，但它会使扫描肌电图信号的生理波形失真。在这项研究中，我们描述了一种新的扫描肌电图信号处理算法，该算法在有效去除其他运动单位干扰的同时保留生理信号波形。为了获得清理后的扫描信号，掩蔽最小二乘平滑（MLSS）算法使用空间维度中的最小二乘平滑重新计算并替换信号的每个样本值，同时仅考虑不受其他运动单元活动污染的样本的信息。研究了新算法对模拟扫描肌电图信号的性能，并与中值算法的性能进行了比较，并对真实扫描信号进行了测试。结果表明，MLSS 算法对扫描肌电图信号的波形失真比中值算法小得多（约 3.5dB 增益），同时在去除干扰分量方面非常有效。
