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An Optimized Selection Method of Channel Numbers and Electrode Layouts for Hand Motion Recognition
International Journal of Humanoid Robotics ( IF 1.5 ) Pub Date : 2019-07-29 , DOI: 10.1142/s0219843619410068
Jiang Hua 1 , Gongfa Li 1 , Du Jiang 2 , Haoyi Zhao 3 , Jinxian Qi 4
Affiliation  

The channel numbers and electrode layouts are usually determined empirically that would reduce robustness when acquiring surface electromyography (EMG) signals for prosthetic hand systems. It is necessary to study how they can be exploited effectively for a more accurate extraction. In response to the problem, an experiment is designed that establishes the relationship between sEMG signals and forearm muscles based on signal-to-noise ratio (SNR). The SNR of sEMG signals in different sampling channels can be calculated and compared, and then the potential contribution of each channel during different hand motions will be evaluated comprehensively. The active muscle regions can be obtained from the established relationship that is a useful reference for feature extraction. Finally, the relations between the computational cost, channel numbers and electrode layouts are explored. The findings of this paper support the idea that the accuracy of pattern recognition will not be affected when reducing the redundant electrodes.

中文翻译:

一种手部动作识别通道数和电极布局的优化选择方法

通道数和电极布局通常根据经验确定,这会降低在获取假手系统的表面肌电图 (EMG) 信号时的稳健性。有必要研究如何有效地利用它们来进行更准确的提取。针对该问题,设计了一项实验,根据信噪比 (SNR) 建立 sEMG 信号与前臂肌肉之间的关系。可以计算和比较不同采样通道的sEMG信号的SNR,进而综合评估各个通道在不同手部动作中的潜在贡献。可以从建立的关系中获得活跃的肌肉区域,这对于特征提取是一个有用的参考。最后,计算成本之间的关系,探索了通道数和电极布局。本文的研究结果支持了减少冗余电极不会影响模式识别准确性的观点。
更新日期:2019-07-29
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