Hand and Finger Control of Myoelectric Prosthesis Hand Based on Motion Discriminator and Voluntary Control
Hand and Finger Control of Myoelectric Prosthesis Hand Based on Motion Discriminator and Voluntary Control
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基于运动判别器和自主控制的肌电假手的手和手指控制
DOI：
10.9746/sicetr.54.680
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
J. Inoue
中科院分区：
文献类型：
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作者：
Risako Hiroki;M. Iwase;J. Inoue
我们的目的是估计手指在屈伸时的角度。采用混合方法估计各指关节角度。并验证了该方法的有效性。该方法是利用支持向量机识别手指运动和估计关节角度的一种方法。在本研究中，我们开发了一种肌电操作肌电假体的环境。利用支持向量机对5个手指运动进行识别，并利用混合方法对每个手指关节运动角1进行了高精度估计。在此基础上对肌电假体进行了操作，证实了肌电假体的操作是符合操作者要求的。因此，混合方法是估计五指关节角度的一种有效方法。在未来，手指动作的识别精度将会提高，手指的2个动作的角度将会被估计。
We aim to estimate angle of finger during flexion and extension. Each finger joint angle is estimated by hybrid method. Moreover, it is verified the method is effectivity. The hybrid method is one of the method to identify finger motions by SVM and to estimate joint angle. In this research, an environment has been developed to be operate myoelectric prosthesis by myoelectric. Moreover, 5 finger motions have been identified by SVM, and it is estimated each finger joint angle of motion 1 with a high accuracy by the hybrid method. The myoelectric prosthesis has been operated based on these results, and it is affirmed the myoelectric prosthesis has been follow the operater. Therefore, the hybrid method is a usable way to estimate 5 finger joint angle. In the future, identification of finger motions will be increased accuracy, and finger angle of 2 motions will be estimated.