Identification of Nonlinear Models of Artificial Stimulation of the Quadriceps Muscle

Abstract

The problem of identification of nonlinear models for the Functional Electrical Stimulation (FES) process is considered. In particular, the stimulation of the quadriceps muscle group and the following movement (or torque release) of the knee-joint will be considered. Both isometric and isotonic experimental conditions are considered. NARX models will be identified from data: polynomial and neural network structures are considered. For both model families, the structural identification problem and the model validation issue are considered. The resulting models are compared with experimental data measured on a paraplegic patient.