Refined myoelectric control in below-elbow amputees using artificial neural networks and a data glove.

Purpose: To develop a system for refined motor control of artificial hands based on multiple electromyographic (EMG) recordings, allowing multiple patterns of hand movements.

Methods: Five subjects with traumatic below-elbow amputations and 1 subject with a congenital below- elbow failure of formation performed 10 imaginary movements with their phantom hand while surface electrodes recorded the EMG data. In a training phase a data glove with 18 degrees of freedom was used for positional recording of movements in the contralateral healthy hand.