Using speech for mode selection in control of multifunctional myoelectric prostheses

Electromyogram (EMG) recorded from residual muscles of limbs is considered as suitable control information for motorized prostheses. However, in case of high-level amputations, the residual muscles are usually limited, which may not provide enough EMG for flexible control of myoelectric prostheses with multiple degrees of freedom of movements. Here, we proposed a control strategy, where the speech signals were used as additional information and combined with the EMG signals to realize more flexible control of multifunctional prostheses. By replacing the traditional “sequential mode-switching (joint-switching)”, the speech signals were used to select a mode (joint) of the prosthetic arm, and then the EMG signals were applied to determine a motion class involved in the selected joint and to execute the motion. Preliminary results from three able-bodied subjects and one transhumeral amputee demonstrated the proposed strategy could achieve a high mode-selection rate and enhance the operation efficiency, suggesting the strategy may improve the control performance of commercial myoelectric prostheses.