Adaptive Filtering for Baseline Wander Noise of ECG Using Neural Networks

摘要

This study proposed the new method to minimize distortion of the ST segment and noise deletion of ECG baseline wander. In general, the standard filter and adaptive filter are used to remove the baseline wander of the ECG. The standard filter, however, is limited because the frequency of the baseline signal is variable and the baseline wander's spectrum overlaps with the ST segment's spectrum, and for the adaptive filter, it is difficult to select the reference signal. This study proposed a new, structured adaptive filter that is to remove noise without reference signal using neural networks. In order to confirm performance, this paper used ECG data of MIT-BIHs and obtained significant results through the tests.