Progress towards the intelligent control of a powered transfemoral prosthesis

Abstract

In this thesis, firstly a real-time gait intent recognition approach for use in controlling a fully powered transfemoral prosthesis is described. 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. Secondly, an active passive torque decomposition procedure for use in controlling a fully powered transfemoral prosthesis is described. The active and passive parts of the joint torques are extracted by solving a constrained least squares optimization problem. The proposed approach generates the torque reference of joints by combining the active part, which is a function of the force and moment vector of the interaction between user and prosthesis and the passive part, which has a nonlinear spring-dashpot behavior. The ability of the approach to reconstruct the required joint torques is again demonstrated in simulation on measured biomechanics data. Finally, the calibration procedure of the three axis socket load cell of the prosthesis' mechanical sensory interface is also presented in the thesis.