Real-time Intent Recognition for a Powered Knee and Ankle Transfemoral Prosthesis

This paper describes a real-time gait intent recognition approach for use in controlling a fully powered transfemoral prosthesis. Rather than utilize an "echo control" as proposed by others, which requires instrumentation of the sound-side leg, the proposed approach infers user intent based on the characteristic shape of the force and moment vector of interaction between the user and prosthesis. The real-time intent recognition approach utilizes a K-nearest neighbor algorithm with majority voting and threshold biasing schemes to increase its robustness. The ability of the approach to recognize in real time a person's intent to stand or walk at one of three different speeds is demonstrated on measured biomechanics data.