- Tytuł:
- Empirical Bayesian averaging method and its application to noise reduction in ECG signal
- Autorzy:
-
Momot, A.
Momot, M.
Łęski, J. - Powiązania:
- https://bibliotekanauki.pl/articles/333575.pdf
- Data publikacji:
- 2006
- Wydawca:
- Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
- Tematy:
-
sygnał EKG
średnia ważona
wnioskowanie bayesowskie
ECG signal
weighted averaging
Bayesian inference - Opis:
- An electrocardiogram (ECG) is the prime tool in non-invasive cardiac electrophysiology and has a prime function in the screening and diagnosis of cardiovascular diseases. However one of the greatest problems is that usually recording an electrical activity of the heart is performed in the presence of noise. The paper presents empirical Bayesian approach to problem of signal averaging which is commonly used to extract a useful signal distorted by a noise. The averaging is especially useful for biomedical signal such as ECG signal, where the spectra of the signal and noise significantly overlap. In reality the variability of noise can be observed, with power from cycle to cycle, which is motivation for weighted averaging methods usage. It is demonstrated that by exploiting a probabilistic Bayesian learning framework, it can be derived accurate prediction models offering significant additional advantage, namely automatic estimation of 'nuisance' parameters. Performance of the new method is experimentally compared to the traditional averaging by using arithmetic mean and weighted averaging method based on criterion function minimization.
- Źródło:
-
Journal of Medical Informatics & Technologies; 2006, 10; 93-101
1642-6037 - Pojawia się w:
- Journal of Medical Informatics & Technologies
- Dostawca treści:
- Biblioteka Nauki
Artykuł