HUMAN-EMG PROSTHETIC HAND INTERFACE USING NEURAL NETWORK |
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| S. Morita, K. Shibata, X.–Z. Zheng, K. Ito |
- Abstract:
- For the improvement of the amputee’s activity of daily living (ADL), several kinds of electromyogram (EMG) controlled prosthetic hands have been developed so far. But there is still significant difference between the movements of these hands and human ones. In this paper, we propose a direct torque control method for the prosthetic hand. In order to estimate the joint torque from EMG signals, an artificial neural network by the feedback error learning schema is used. 2- DOF motions, i.e. hand grasping/opening and arm flexion/extension, are picked up. Then it is verified that the neural network can learn the relation between the EMG signal and joint torque.
- Keywords:
- prosthetic hand, neural network, EMG signal
- Download:
- IMEKO-WC-2000-TC13-P338.pdf
- DOI:
- -
- Event details
- Event name:
- XVI IMEKO World Congress
- Title:
Measurement - Supports Science - Improves Technology - Protects Environment ... and Provides Employment - Now and in the Future
- Place:
- Vienna, AUSTRIA
- Time:
- 25 September 2000 - 28 September 2000