假手肌电控制的递归神经网络模型

2018 22nd International Conference on System Theory, Control and Computing (ICSTCC) Pub Date : 2018-10-01 DOI:10.1109/ICSTCC.2018.8540720

Teodor-Adrian Teban, R. Precup, Elena-Cristina Lunca, A. Albu, Claudia-Adina Bojan-Dragos, E. Petriu

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引用次数: 15

摘要

本文提出了一套基于表面肌电传感器的递归神经网络(RNNs)，能够复制假手的非线性机制。实验结果表明，该系统对训练数据有较好的处理效果，对验证数据有较好的处理效果。将已开发的rnn与类似大小的非循环神经网络进行比较。

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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Recurrent Neural Network Models for Myoelectricbased Control of a Prosthetic Hand

This paper proposes a set of recurrent neural networks (RNNs) capable of replicating the non-linear mechanism of a prosthetic hand based on surface myoelectric sensors. The experimental results of the RNN show a good result of the system for the training data and an acceptable result on the validation data. A comparison between the developed RNNs and a similar size non-recurrent neural network is included.

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2018 22nd International Conference on System Theory, Control and Computing (ICSTCC)

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