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ECG denoising using angular velocity as a state and an observation in an Extended Kalman Filter framework

Akhbari, M ; Sharif University of Technology | 2012

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  1. Type of Document: Article
  2. DOI: 10.1109/EMBC.2012.6346569
  3. Publisher: 2012
  4. Abstract:
  5. 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
  6. Keywords:
  7. Denoising ; ECG Dynamical Model ; Electrocardiogram (ECG) ; Extended Kalman Filter (EKF) ; Ecg dynamical models ; ECG signals ; Filtering procedures ; Normal sinus rhythm ; Observation equation ; Quantitative evaluation ; SNR improvement ; Angular velocity ; Electrocardiography ; Extended Kalman filters
  8. Source: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS ; 2012 , Pages 2897-2900 ; 1557170X (ISSN) ; 9781424441198 (ISBN)
  9. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6346569