Human Gait Analysed by an Artificial Neural Network Model

In this paper a model proposed by Sepulveda et al. [1] will be revised regarding the use of artificial neural networks to map EMG signals and joint dynamics in the lower-limb. The original model will be used to analyse other aspects of human gait, like muscle recruitment, movement patterns and to study a problem from a patient with a lesion in the femur's region. Some theory on neural networks is applied to validate the model and train the network. New tests are used to verify other aspects of the human gait study. Analysis of the results showed some discrepancies in EMG/moments mapping but good results in