Training of grasping motion using a virtual prosthetic control system

Electromyogram (EMG) signals can be measured from human muscles and can be used to anticipate movements. In fact, many researchers have tried to use these signals as an interface tool for a prosthetic hand. However, most of these studies focused on the discrimination performance of the EMG signals, and only discussed the control method for the prosthetic hand. Evaluation of the operating performance while the operator wore the prosthetic hand was seldom reported. This paper proposes a virtual prosthetic control system and presents the analyses of a grasp motion under two different EMG control methods: ON-OFF Digital Control (Digital) and Dynamic Mode Control (DMC). DMC is able to proportionally control the grasping velocity based on the amplitude of the EMG signal. Digital controls the hand at a uniform rate while the amplitude of the EMG signal is greater than a predefined threshold. We conducted experiments with five subjects, and confirmed the usefulness of the developed system.