ECG Denoising using Angular Velocity as a State and an Observation in an Extended Kalman Filter Framework

Mahsa Akhbari (1, 2) , Mohammad B. Shamsollahi (1) , Christian Jutten (2) , Bertrand Coppa (3)

1 BiSIPL - Biomedical Signal and Image Processing Laboratory [Teheran]
2 GIPSA-VIBS - GIPSA - Vision and Brain Signal Processing
3 CEA-LETI - Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information

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.

Mots clés: Extended Kalman Filter (EKF); Angular velocity; Electrocardiogram (ECG); ECG Dynamical Model; Denoising

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Mahsa Akhbari, Mohammad B. Shamsollahi, Christian Jutten, Bertrand Coppa. ECG Denoising using Angular Velocity as a State and an Observation in an Extended Kalman Filter Framework. EMBC 2012 - 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Aug 2012, San Diego, Californie, United States. pp.2897-2900, ⟨10.1109/EMBC.2012.6346569⟩. ⟨hal-00853756⟩