The proposed EKF-based filtering procedure with a modified nonlinear dynamic model significantly improves ECG signal denoising compared to standard EKF.
May aid ECG denoising in noisy settings; leaves open clinical validation before practice change.
In this paper an efficient filtering 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.
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Sayadi et al. (2007) studied this question.
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