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Pattern recognition of electromyography applied to Exoskeleton Robot

机译:肌电学的模式识别应用于外骨骼机器人

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Exoskeleton Robot is a robotic-assisted human-machine system, which can provide power to assist the movement of people. This paper aims to find a method of EMG pattern recognition used in Exoskeleton Robot. To the beginning, the EMG power spectrum ratio (PSR) is calculated as the EMG eigenvalue. Then the minimum error-based Bayes decision rule is used to determine the movement intention of human, implemented in Matlab. The research result shows that the power spectrum density rate and the minimum error-based Bayesian decision theory can recognize the EMG on the movement intention of lower extremity exoskeleton with the advantages of easy reality and fast compute by Matlab.
机译:外骨骼机器人是一个机器人辅助人机系统,可以提供有助于人们运动的动力。本文旨在找到一种用于外骨骼机器人的EMG模式识别方法。到开始,EMG功率谱比(PSR)被计算为EMG特征值。然后使用最小的基于误差的贝母决策规则来确定人类的运动意向,在Matlab中实施。研究结果表明,功率谱密度率和最小的基于误差的贝叶斯决策理论可以识别下肢外骨骼的运动意向,具有易于现实的优点和Matlab的快速计算。

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