Extraction of event-related signals from multichannel bioelectrical measurements

Independent component analysis (ICA) is a powerful tool for separating signals from their mixtures. In this field, many algorithms were proposed, but they poorly use a priori information in order to find the desired signal. Here, we propose a fixed point algorithm which uses a priori information to find the signal of interest out of a number of sensors. We particularly applied the algorithm to cancel cardiac artifacts from a magnetoencephalogram.