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Poster:Development of dynamic leg joint model for paraplegic with Functional Electrical Stimulation

This paper presents the development of paraplegic joint model using Artificial Neural Network (ANN). A series of experiments using Functional Electrical Stimulation (FES) with different stimulation frequencies, pulse width and pulse duration to investigate the impact on the leg swing angle is conducted. The data obtained is used to develop the paraplegic leg joint model. 74810 training data and 33602 testing data set are used in the development of joint model. The joint model thus developed is validated with clinical data from one paraplegic subject. Two modelling strategies were used to model the leg joint which the ANN joint model is found to be the most useful joint model representing paraplegic leg. The established model is then used to predict the behaviour of the underlying system and will be used in the future for the design and evaluation of various control strategies.