AUTHORS: Carlos Lastre-Dominguez, Yuriy S. Shmaliy, Oscar Ibarra-Manzano

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ABSTRACT: Heart diseases are one of most frequent causes of death in the modern world. Therefore, the ECG signal features have been under peer review for decades to improve medical diagnostics. In this paper, we provide smoothing of the atrial premature complex (APC) of the electrocardiogram (ECG) signal using unbiased finite impulse response (UFIR) smoothing filtering. We investigate the P-wave distribution using the Rice law and determine the probabilistic confidence interval based on a database associated with normal heartbeats. It is shown that the abnormality in the APC is related to the P-wave morphology. Different filtering techniques employing predictive and smoothing filtering are applied to APC data and compared experimentally. It is demonstrated that UFIR smoothing provides better performance among others. We finally show that the P-wave confidence interval defined for the Rice distribution can be used to provide an automatic diagnosis with a given probability.

KEYWORDS: Atrial premature complex, UFIR smoothing, electrocardiogram, Rice distribution, confidence interval

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