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ECG denoising using angular velocity as a state and an observation in an Extended Kalman Filter framework.
- Source :
-
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2012; Vol. 2012, pp. 2897-900. - Publication Year :
- 2012
-
Abstract
- In this paper an efficient filtering procedure based on Extended Kalman Filter (EKF) has been proposed. The method is based on a modified nonlinear dynamic model, previously introduced for the generation of synthetic ECG signals. The proposed method considers the angular velocity of ECG signal, as one of the states of an EKF. We have considered two cases for observation equations, in one case we have assumed a corresponding observation to angular velocity state and in the other case, we have not assumed any observations for it. Quantitative evaluation of the proposed algorithm on the MIT-BIH Normal Sinus Rhythm Database (NSRDB) shows that an average SNR improvement of 8 dB is achieved for an input signal of -4 dB.
- Subjects :
- Humans
Models, Theoretical
Algorithms
Electrocardiography methods
Subjects
Details
- Language :
- English
- ISSN :
- 2694-0604
- Volume :
- 2012
- Database :
- MEDLINE
- Journal :
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
- Publication Type :
- Academic Journal
- Accession number :
- 23366530
- Full Text :
- https://doi.org/10.1109/EMBC.2012.6346569