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Pattern recognition of electromyography applied to Exoskeleton Robot

机译:应用于外骨骼机器人的肌电图模式识别

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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:外骨骼机器人是机器人辅助的人机系统,可以提供帮助人员移动的动力。本文旨在寻找一种用于外骨骼机器人的肌电图模式识别方法。首先,将EMG功率谱比(PSR)计算为EMG特征值。然后,基于最小误差的贝叶斯决策规则用于确定人的运动意图,并在Matlab中实现。研究结果表明,功率谱密度比率和基于最小误差的贝叶斯决策理论可以识别下肢外骨骼运动意图的肌电图,具有易于实现和Matlab快速计算的优点。

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