Abstract
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.
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