Independent Component Analysis using wavelet transform and its application to biological signals

Abstract

Independent Component Analysis (ICA) is a useful method for blind source separation of two signals or more. We have previously proposed a new method combining ICA with the complex discrete wavelet transform (CDWT). In this case, the voice and the noise were separated using a new method. At that time, we used the simulation signal. In this study, we analyze measured biological signals by using this new method, and discuss its effectiveness. As an example, we tried the separation of the EMG signal and the ECG signal.