Myoelectric neural interface enables accurate control of a virtual multiple degree-of-freedom foot-ankle prosthesis.

Technological advances have enabled clinical use of powered foot-ankle prostheses. Although the fundamental purposes of such devices are to restore natural gait and reduce energy expenditure by amputees during walking, these powered prostheses enable further restoration of ankle function through possible voluntary control of the powered joints. Such control would greatly assist amputees in daily tasks such as reaching, dressing, or simple limb repositioning for comfort. A myoelectric interface between an amputee and the powered foot-ankle prostheses may provide the required control signals for accurate control of multiple degrees of freedom of the ankle joint. Using a pattern recognition classifier we compared the error rates of predicting up to 7 different ankle-joint movements using electromyographic (EMG) signals collected from below-knee, as well as below-knee combined with above-knee muscles of 12 trans-tibial amputee and 5 control subjects. Our findings suggest very accurate (5.3 ± 0.5%SE mean error) real-time control of a 1 degree of freedom (DOF) of ankle joint can be achieved by amputees using EMG from as few as 4 below-knee muscles. Reliable control (9.8 ± 0.7%SE mean error) of 3 DOFs can be achieved using EMG from 8 below-knee and above-knee muscles.