The pattern classification of motor unit action pote ntia l (MUAP) of needle electrode electromyogram (NEMG) signal by means of self-orga nization competing Neural Network(NN) has been accomplished in this paper. The p arameters and the power of excited white-noise of auto-regressive (AR) model a re taken as the feature of MUAP. The results of simulated NEMG and real NEMG all show that this method of classification is very effective and correct, and thus it presents a new approach to the extraction of MUAP template in the study of decomposition of NEMG.
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