Prediction of Lower Extremity Movement by Cyclograms

P. Kutilek, S. Viteckova


Human gait is nowadays undergoing extensive analysis. Predictions of leg movements can be used for orthosis and prosthesis programming, and also for rehabilitation. Our work focuses on predicting human gait with the use of angle-angle diagrams, also called cyclograms. In conjunction with artificial intelligence, cyclograms offer a wide area of medical applications. We have identified cyclogram characteristics such as the slope and the area of the cyclogram for a neural network learning algorithm. Neural networks learned by cyclograms offer wide applications in prosthesis control systems.


gait; artificial intelligence; cyclogram; artificial neural networks

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ISSN 1210-2709 (Print)
ISSN 1805-2363 (Online)
Published by the Czech Technical University in Prague