Beamforming for Powerline Interference in Large Sensor Arrays

Manouane Caza-Szoka, D. Massicotte, F. Nougarou
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Abstract

This paper shows how to use beamforming to remove the power-line interference (PLI) in large surface electromyography (sEMG) sensor array or high-density sEMG. The method exploits the highly correlated nature of the different sources of interference, being part of the same electrical grid, and their narrow frequency bands. The idea is to use a very narrow pass-band filter around 50 or 60 Hz to get signals with high PLI content before applying a spatial filtering by principal component analysis (PCA). This way, beamforming are done on the frequency bands where PLI are presents. Also, it ensures that even if the PLI has a smaller overall power than the desired signal, it will be easily found as the most powerful component of the decomposition. The PLI can then be removed from the signal. With trivial modification, harmonics of the PLI can also be removed. The approach was used in the context of muscle behavior analyses of low back pain patients using a sEMG array of 64 sensors. The performances of the filter are studied by experimental and semi-empirical methods. Compared to the usual notch filter, an improvement of up 10 dB is found.
大型传感器阵列中电力线干扰的波束形成
本文介绍了如何利用波束形成技术消除大表面肌电信号传感器阵列或高密度表面肌电信号中的电力线干扰。该方法利用了属于同一电网的不同干扰源的高度相关性质,以及它们的窄频带。这个想法是在应用主成分分析(PCA)的空间滤波之前,使用大约50或60 Hz的非常窄的通带滤波器来获得具有高PLI内容的信号。这样,波束形成是在PLI存在的频段上完成的。此外,它确保即使PLI的总功率小于所需信号,它也很容易被发现是分解中最强大的组成部分。然后可以将PLI从信号中移除。通过简单的修改,PLI的谐波也可以被去除。该方法被用于腰痛患者的肌肉行为分析,使用64个传感器的表面肌电信号阵列。采用实验和半经验方法研究了该滤波器的性能。与通常的陷波滤波器相比,改进幅度高达10 dB。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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