SOURCE SEPARATION FROM SINGLE CHANNEL BIOMEDICAL SIGNAL BYCOMBINATION OF BLIND SOURCE SEPARATION AND EMPIRICAL MODE DECOMPOSITION

These days, Blind Source Separation (BSS) techniques are the most common and beneficial method, in signal processing. In the field of multichannel recording, over the past years, many techniques of BSS are introduced which can work accurately, in contrast to the multichannel recording, in the single channel measurement, only a few methods are existed. One of the much popular algorithms of BSS is Independent Component Analysis (ICA) which applies to separate the independent components from multi channel measurements. In this paper, we proposed two new algorithms to separate the mixed sources in single channel recording. We named our methods: Automated EE-ICA and EE-ICA with post processing; these methods are based on composing the Empirical Mode Decomposition (EMD) and ICA in a new manner. EMD is a technique for splitting up the single channel signal into its components. We will investigate the performance of our methods in the field of biomedical signals.