Prediction of Lower Extremity Movement by Cyclograms

Authors

  • P. Kutilek
  • S. Viteckova

DOI:

https://doi.org/10.14311/1514

Keywords:

gait, artificial intelligence, cyclogram, artificial neural networks

Abstract

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.

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Author Biographies

P. Kutilek

S. Viteckova

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Published

2012-01-01

How to Cite

Kutilek, P., & Viteckova, S. (2012). Prediction of Lower Extremity Movement by Cyclograms. Acta Polytechnica, 52(1). https://doi.org/10.14311/1514

Issue

Section

Articles