Multichannel adaptive filtering using an efficient matching pursuit-like algorithm for removal of CPR artifacts in ECG signals

In this contribution we present a novel algorithm for multichannel adaptive filtering. The algorithm is based on selective update of filter coefficients using a matching pursuit-like strategy operating on a time varying “dictionary” given by the current multichannel data matrix. The algorithm has low computational complexity and is robust in rank deficient situations. We present the adaptive filter in an application oriented setting in which the objective is to remove artifacts in electrocardiograms (ECG) resulting from cardiopulmonary resuscitation (CPR). We present simulation results on realistic data showing the superior performance of the algorithm.