Abstract: Current methods of prosthesis control are overly simplistic, using two opposing electromyographic control signals to control the prosthetic hand, normally with no finger control. Recent research has demonstrated that mechanomyographic (MMG) signals can do the same. This experiment investigates the possibility of fusing multiple MMG signals to create a control scheme for prostheses that provides control over groups of fingers. Concurrent recordings of MMG activity and finger motions were made during several finger movements. The recordings were ...
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Topics: 
Artificial intelligence
Computer vision