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Application of filtering methods for removal of resuscitation artifacts from human ECG signals
Ivan Markovsky1, Anton Amann, Sabine Van Huffel
1School of Electronics and Computer Science, University of Southampton, SO17 1BJ, UK. im@ecs.soton.ac.uk
Abstract:
Band-pass, Kalman, and adaptive filters are used for removal of resuscitation artifacts from human ECG signals. A database of separately recorded human ECG and animal resuscitation artifact signals is used for evaluation of the methods. The considered performance criterion is the signal-to-noise ratio (SNR) improvement, defined as the ratio of the SNRs of the filtered signal and the given ECG signal. The empirical results show that for low SNR of the given signal, a band-pass filter yields the best performance, while for high SNR, an adaptive filter yields the best performance.
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