Towards an evolutionary neural network for gait analysis

This paper presents initial investigations into an evolutionary neural network suitable for gait analysis of human motion. The approach here is to develop an intelligent black box that can take the physiological signals (EMG) and interpret them to give accurate information on the position and movement of the knee (gait). Two MLP networks are presented with weight evolving algorithms employing mutation and crossover separately. Simulation results show the evolutionary algorithms exhibiting particularly better ability to generalise solutions, which is an important aspect for the reliability of EMG/gait map generation