International Journal of Precision Engineering and Manufacturing

Korean Society for Precision Engineering (한국정밀공학회)
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Adaptive Postural Control for Trans-Femoral Prostheses Based on Neural Networks and EMG Signals

  • Lee Ju-Won (Depart. of Electronic Engineering, Gyeongsang National University) ;
  • Lee Gun-Ki (Depart. of Electronic Engineering, Gyeongsang National University)
  • Published : 2005.07.01
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Abstract

Gait control capacity for most trans-femoral prostheses is significantly different from that of a normal person, and training is required for a long period of time in order for a patient to walk properly. People become easily tired when wearing a prosthesis or orthosis for a long period typically because the gait angle cannot be smoothly adjusted during wearing. Therefore, to improve the gait control problems of a trans-femoral prosthesis, the proper gait angle is estimated through surface EMG(electromyogram) signals on a normal leg, then the gait posture which the trans-femoral prosthesis should take is calculated in the neural network, which learns the gait kinetics on the basis of the normal leg's gait angle. Based on this predicted angle, a postural control method is proposed and tested adaptively following the patient's gait habit based on the predicted angle. In this study, the gait angle prediction showed accuracy of over $97\%$, and the posture control capacity of over $90\%$.

Keywords

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