Abstract

It is recognized that one of the main causes of human death is associated with heart disease. An electrocardiogram (ECG) is used to identify abnormalities related to the electrical activities of the heart. In this paper, we discuss applications of the unbiased finite impulse response (UFIR) estimation approach to denoise the ECG measurements and extract useful features from. One of the standard methods providing denoising and extracting features of the ECG signals is based on the one-step prediction. We show that better accuracy can be obtained by using the UFIR filter and the UFIR smoothing filter with adaptive averaging horizon length.

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