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Simultaneous and Proportional Estimation of Finger Joint Angles from Surface EMG Signals during Mirrored Bilateral Movements

机译:镜像双边运动期间从表面EMG信号的同时和比例估计

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This paper studies the continuous estimation of finger angles with state-space model to realize the simultaneous and proportional control of finger joint motions, where the test model of mirrored bilateral movements is first applied to decode the fingers’ continuous motion. First a linear method was proposed for simultaneous and proportional estimation of 10 degrees of freedom (DOFs) finger joint angle with surface eletromyography (EMG). The state-space model was adopted to estimate one finger joint angle from 8 channel surface EMG signals recorded from contralateral limb mirrored bilateral movements. The average estimation performance of 8 DOFs of the hand except little finger can achieve 0.824(index R2), while the index R2 can achieve as high as 0.924 with the estimation thumb metacarpophalangeal joint (MCP). Although the estimation performance of the little finger was not good enough, the results demonstrate that state-space model is a feasible method to estimate the finger joint angles. Because the proposed method requires only the contralateral finger joint angles as the model identification reference, there is a great potential application for unilateral amputees in control of dexterous myoelectric prosthesis with multiple DOFs.
机译:本文研究了与状态空间模型的手指角度的连续估计,以实现手指联合运动的同时和比例控制,其中首先应用镜像双边运动的测试模型来解码手指的连续运动。首先,提出了一种线性方法,用于与表面弹性成像(EMG)的10度自由度(DOFS)指关节角度同时和比例估计。采用状态空间模型从对侧肢体镜像双边运动记录的8个通道表面EMG信号估计一个手指接头角度。除了小指外,手的8个DOF的平均估计性能可以实现0.824(指数R2),而指数R2可以通过估计拇指Metacarpophalangeal关节(MCP)达到0.924。虽然小指的估计性能不够好,但结果表明,状态空间模型是估计手指关节角度的可行方法。因为所提出的方法只需要对侧指向的关节角度作为模型识别参考,所以对具有多个DOF的Dexerous肌电假体控制的单侧和单侧核心有很大的潜在应用。

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