Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
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A Study on Function Discrimination for EMG Signals Using Neural Network and Fuzzy Filter

신경회로망과 퍼지필터를 사용한 근전도신호의 기능변별에 관한 연구

  • 장영건 (인하대학교 전자공학과) ;
  • 홍승홍 (인하대학교 전자공학과)
  • Published : 1994.09.01
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Abstract

The most important requirement for the controller of a prosthetic arm is that it has a high fidelity discriminator where the motion control may be performed open loop using EMG signals as a control source. Therefore, it is very effective method to reduce the influence of misclassification of classifier for the total system performance. This paper presents the new function discrimination method which combines MLP classifier and frizzy filter by stages for the requirement. The major advantage of MLP is a consistent learning capability for the easy adaptation to environments. The fuzzy filter uses all informations of MLP outputs and prior EMG activity informations which increase as the experience increases. That property is superior to one which uses maximum output of MLP in view of information amounts and quality. Simulation result shows that proposed method is superior to the probabilistic model, MLP model and the combined model of both in the respect of discrimination quaity.

Keywords

References

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