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Estimation of Optimal Measurement Position of Human Forearm EMG Signal by Discriminant Analysis Based on Wilks' Lambda

机译:基于Wilks Lambda判别分析的人体前臂肌电信号最佳测量位置估计

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This paper describes the estimation of the optimal measurement position by discriminant analysis based on Wilks' lambda for myoelectric hand control. In previous studies, for motion discrimination, the myoelectric signals were measured at the same positions. However, the optimal measurement positions of the myoelectric signals for motion discrimination differ depending on the remaining muscles of amputees. Therefore, the purpose of this study is to estimate the optimal and fewer measurement positions for precise motion discrimination of a human forearm. This study proposes a method for estimating the optimal measurement positions by discriminant analysis based on Wilks' lambda, using the myoelectric signals measured at multiple positions. The results of some experiments on the myoelectric hand simulator show the effectiveness of the proposed optimal measurement position estimation method.
机译:本文介绍了基于判别分析的最佳测量位置估计,该判别分析基于Wilks的lambda用于肌电手控制。在先前的研究中,为了进行运动识别,在相同位置测量了肌电信号。然而,用于运动辨别的肌电信号的最佳测量位置取决于截肢者的剩余肌肉。因此,本研究的目的是估计用于精确区分人前臂的最佳和较少的测量位置。这项研究提出了一种基于判别分析的最佳测量位置估计方法,该判别分析基于Wilksλ,使用在多个位置测量的肌电信号。在肌电手模拟器上进行的一些实验结果表明,所提出的最佳测量位置估计方法是有效的。

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