An EMG classifying method based on Bayes' criterion

To counter the applied request of electromyography prosthesis and the characteristics of EMG signal, a method of EMG pattern recognition based on Bayes' criterion is presented. Two constraints of probability and time domain parameters are given to reduce the error rate of the prosthetic action. From the experiment to real EMG signals, this method is proved to be applicable to the control of EMG prosthesis.

[1]  Arnon D. Cohen,et al.  Biomedical Signal Processing , 1986 .

[2]  R. B. Knapp,et al.  Real-time computer control using pattern recognition of the electromyogram , 1993, Proceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology Societ.

[3]  A. Willsky,et al.  Upper Extremity Limb Function Discrimination Using EMG Signal Analysis , 1983, IEEE Transactions on Biomedical Engineering.

[4]  Daniel Graupe,et al.  Functional Separation of EMG Signals via ARMA Identification Methods for Prosthesis Control Purposes , 1975, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  Chenglin Peng,et al.  Applying Bayes' theorem in medical expert systems , 1996 .