Loading...

ECG denoising using parameters of ECG dynamical model as the states of an extended Kalman filter

Sayadi, O ; Sharif University of Technology | 2007

346 Viewed
  1. Type of Document: Article
  2. DOI: 10.1109/IEMBS.2007.4352848
  3. Publisher: 2007
  4. Abstract:
  5. In this paper an efficient Altering procedure based on the 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. We have suggested simple dynamics as the governing equations for the model parameters. Since we have not any observation for these new state variables, they are considered as hidden states. Quantitative evaluation of the proposed algorithm on the MIT-BIH signals shows that an average SNR improvement of 12 dB is achieved for a signal of -5 dB. The results show improved output SNRs compared to the EKF outputs in the absence of these new dynamics. © 2007 IEEE
  6. Keywords:
  7. Extended Kalman filters ; Mathematical models ; Nonlinear analysis ; Signal to noise ratio ; ECG denoising ; Hidden state variable ; Electrocardiography ; Algorithm ; Biological model ; Computer program ; Methodology ; Signal processing ; Algorithms ; Electrocardiography ; Models, biological ; Signal processing, computer-assisted ; Software
  8. Source: 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07, Lyon, 23 August 2007 through 26 August 2007 ; 2007 , Pages 2548-2551 ; 05891019 (ISSN) ; 1424407885 (ISBN); 9781424407880 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/4352848?arnumber=4352848