Electromyography signal can be used for biomedical applications. It is complicated in interpretation, so it acquires advanced methods for detection, decomposition, processing, and classification. The techniques of EMG signal analysis such as: filtering, wavelet transform, and modeling will be presented in this paper to provide efficient and effective ways of understanding the signal. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help to develop more flexible and efficient application