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Clinical myography(EMG) is a technique for diagnosing neuromuscular disorders by analyzing the electrical signal that can be records by needle electrode during a muscular contraction. The EMG signal arises from electrical discharges that accompany the generation of force by groups of muscular fiber, and the analysis of EMG signal provides symptoms that can distinguish disorder of mLecle from disor- ders of nerve. One of the methods for analysis of EMG signal is to separate the individual discharge-the motor unit action potentials(MVAPS) - from EMG signal. But we can only observe the EMG signal that is a superimposed version of time delayed MUAPS. To obtain the information about MUAP(,i.e., position, firing number, magnitude etc), first of all, a method that can separate each MUAP from the EMG signal must be developed Although the methods for MUAP separation have been proposed by many researcherl they have required heavy computational burden. In this paper, we proposed a new method that has less computational burden and performs more reliable separation of superimposed EMG signal using wavelet filter which has multiresolution analysis as major property. As a result, we develope the separation algorithm of superimposed EMG signal which has less computational burden than any other researchers and exacutes exact separation process. The performance of this method has been discussed in the automatic resolving procedure which is neccessary to identify every firing of every motor unit from the EMG pattern.
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