A virtual prosthetic hand using EMG signals for fMRI measurements

This paper proposes a virtual EMG-prosthetic hand system using a neural network available in an fMRI room. A subject attaches surface electrodes on his forearm, and manipulates the virtual EMG-prosthetic hand visualized with 3D computer graphics by using visual biofeedback projected on a screen in the scan room. The preliminary experiments demonstrate that the intended hand motion by the subject can be determined with high discrimination rates over 96% without decaying fMRI images. Finally, in order to show the validity of the proposed system, we report the neurological experiments that were carried out to analyze human brain functions.