- Tytuł:
- Characteristic points detection in ECG signal using Bayesian learning and fuzzy system
- Autorzy:
-
Momot, M.
Momot, A. - Powiązania:
- https://bibliotekanauki.pl/articles/333840.pdf
- Data publikacji:
- 2007
- Wydawca:
- Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
- Tematy:
-
sygnał EKG
systemy rozmyte
ECG signal
fuzzy systems
bayesian learning - Opis:
- Characteristic points detection such as beginnings and ends of P-wave, T-wave or QRS complex is one of primary aims in automated analysis of ECG signal. The paper presents one possible approach based on Bayesian inference to design of kernel based classifier. The classification function is constructed using the probability distribution function of standard normal distribution and independent Gaussian random variables. The parameters of such variables are computed using iterative Expectation-Maximization algorithm. This approach is used to calculate parameters of classification function to modelling Takagi-Sugeno-Kang fuzzy systems. Numerical experiment of characteristic points detection in ECG signal using CTS database is also presented.
- Źródło:
-
Journal of Medical Informatics & Technologies; 2007, 11; 171-176
1642-6037 - Pojawia się w:
- Journal of Medical Informatics & Technologies
- Dostawca treści:
- Biblioteka Nauki
Artykuł