| Title |
A Study on the EMG Pattern Recognition Using SOM-TVC Method Robust to System Noise |
| Authors |
김인수(Kim In-Soo) ; 이진(Lee Jin) ; 김성환(Kim Sung-Hwan) |
| Keywords |
EMG Pattern Recognition ; Neural Network ; Eigenvalue ; Additive Nnoise and SOM-TVC |
| Abstract |
This paper presents an EMG pattern classification method to identify motion commands for the control of the artificial arm by SOM-TVC(self organizing map - tracking Voronoi cell) based on neural network with a feature parameter. The eigenvalue is extracted as a feature parameter from the EMG signals and Voronoi cells is used to define each pattern boundary in the pattern recognition space. And a TVC algorithm is designed to track the movement of the Voronoi cell varying as the condition of additive noise. Results are presented to support the efficiency of the proposed SOM-TVC algorithm for EMG pattern recognition and compared with the conventional EDM and BPNN methods. |