Recognition of myoelectric activity based on Teager-Kaiser energy operator

A. Ramírez-García, I. Bazán
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引用次数: 1

Abstract

A challenge in myoelectric control for electrical prosthesis is to obtain information from myoelectric signals to activate the degrees of freedom of the prosthesis. When only a little muscular surface is disposable to detect the myoelectric signal the problem is not easy to solve because only one or two channels can be recorded. So, when only a pair of electrodes or one channel is used to record the signal, strategies to extract more information from the signals should be developed. Then more than one function could be activated in a myoelectric prosthesis. In this paper the Teager-Kaiser energy operator is evaluated in the task of myoelectric signal recognition. Specifically two levels of signal were identified: level 1 (87.37 percent of classification) and level 2 (84.09 percent of classification).
基于Teager-Kaiser能量算子的肌电活动识别
电义肢肌电控制的难点在于如何从肌电信号中获取信息来激活义肢的自由度。当只用一小块肌肉表面来检测肌电信号时,由于只能记录一个或两个通道,因此问题不容易解决。因此,当仅使用一对电极或一个通道来记录信号时,应该开发从信号中提取更多信息的策略。这样,肌电义肢就可以激活不止一种功能。本文对Teager-Kaiser能量算子在肌电信号识别中的应用进行了评价。具体来说,确定了两个级别的信号:1级(87.37%的分类)和2级(84.09%的分类)。
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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