EMG Signal Decoded Based Virtual Artificial Intelligence Hand Control System

被引：0

作者：

Yu, Long ^{[1
]}

Gen, Yanjuan ^{[1
]}

Tao, Dandan ^{[1
]}

Zhou, Guodong ^{[1
]}

Chen, Liang ^{[1
]}

Li, Guanglin ^{[1
]}

Wu, Lushen ^{[2
]}

机构：

[1] Univ Town Shenzhen, 1068 Xueyuan Blvd, Shenzhen 518055, Peoples R China

[2] Univ Nanchang, Sch Mechatron Engn, Nanchang, Jiangxi, Peoples R China

来源：

COMPUTATIONAL MATERIALS SCIENCE, PTS 1-3 | 2011年 / 268-270卷

关键词：

Electromyography; virtual reality technology; multifunctional prosthesis control; Artificial intelligence;

D O I：

10.4028/www.scientific.net/AMR.268-270.422

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

An electromyography (EMG) decoded based virtual artificial intelligence control system has been developed to quantify the performance of real-time control of a multifunctional myoelectric prosthesis. To develop this platform system, a three-dimensional upper limb was simulated by using Solidworks and then implemented into an integrated scene of virtual artificial limb,which was programmed in virtual reality modeling language (VRML) and performed through Simulink toolbox of the MATLAB. By decoding surface electromyography (sEMG) signals collected from arm muscle surface, the platform system can identify thesix classes of different arm and hand movements and control the virtual artificial limb and/or the physical arms simultaneously. The VR-based platform also provides a relaxant and enjoyable training environment for prosthesis-users in clinic.

引用

页码：422 / +

页数：2

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