@InProceedings{6952940,
  author = {M. Akhbari and M. B. Shamsollahi and C. Jutten},
  booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},
  title = {Twave alternans detection in ecg using Extended Kalman Filter and dualrate EKF},
  year = {2014},
  pages = {2500-2504},
  abstract = {T Wave Alternans (TWA) is considered as an indicator of Sudden Cardiac Death (SCD). In this paper for TWA detection, a method based on a nonlinear dynamic model is presented. For estimating the model parameters, we use an Extended Kalman Filter (EKF). We propose EKF6 and dualrate EKF6 approaches. Dualrate EKF is suitable for modeling the states which are not updated in all time instances. Quantitative and qualitative evaluations of the proposed method have been done on TWA challenge database. We compare our method with that proposed by Sieed et al. in TWA challenge 2008. We also compare our method with our previous proposed approach (EKF25-4obs). Results show that the proposed method can detect peak position and amplitude of T waves in ECG precisely. Mean and standard deviation of estimation error of our method for finding position of T waves do not exceed four samples (8 msec).},
  keywords = {electrocardiography;Kalman filters;medical signal processing;nonlinear filters;T wave alternans detection;ECG;extended KALMAN filter;dualrate EKF;TWA detection;nonlinear dynamic model;dualrate EKF6 approach;quantitative evaluation;qualitative evaluation;position detection;electrocardiogram;sudden cardiac death;SCD;Electrocardiography;Kalman filters;Mathematical model;Databases;Noise reduction;Equations;Time measurement;Electrocardiogram (ECG);TWave Alternans (TWA);Extended Kalman Filter (EKF);Dualrate EKF},
  issn = {2076-1465},
  month = {Sep.},
}

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We propose EKF6 and dualrate EKF6 approaches. Dualrate EKF is suitable for modeling the states which are not updated in all time instances. Quantitative and qualitative evaluations of the proposed method have been done on TWA challenge database. We compare our method with that proposed by Sieed et al. in TWA challenge 2008. We also compare our method with our previous proposed approach (EKF25-4obs). Results show that the proposed method can detect peak position and amplitude of T waves in ECG precisely. Mean and standard deviation of estimation error of our method for finding position of T waves do not exceed four samples (8 msec).","keywords":"electrocardiography;Kalman filters;medical signal processing;nonlinear filters;T wave alternans detection;ECG;extended KALMAN filter;dualrate EKF;TWA detection;nonlinear dynamic model;dualrate EKF6 approach;quantitative evaluation;qualitative evaluation;position detection;electrocardiogram;sudden cardiac death;SCD;Electrocardiography;Kalman filters;Mathematical model;Databases;Noise reduction;Equations;Time measurement;Electrocardiogram (ECG);TWave Alternans (TWA);Extended Kalman Filter (EKF);Dualrate EKF","issn":"2076-1465","month":"Sep.","bibtex":"@InProceedings{6952940,\n author = {M. Akhbari and M. B. Shamsollahi and C. Jutten},\n booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},\n title = {Twave alternans detection in ecg using Extended Kalman Filter and dualrate EKF},\n year = {2014},\n pages = {2500-2504},\n abstract = {T Wave Alternans (TWA) is considered as an indicator of Sudden Cardiac Death (SCD). In this paper for TWA detection, a method based on a nonlinear dynamic model is presented. For estimating the model parameters, we use an Extended Kalman Filter (EKF). We propose EKF6 and dualrate EKF6 approaches. Dualrate EKF is suitable for modeling the states which are not updated in all time instances. Quantitative and qualitative evaluations of the proposed method have been done on TWA challenge database. We compare our method with that proposed by Sieed et al. in TWA challenge 2008. We also compare our method with our previous proposed approach (EKF25-4obs). Results show that the proposed method can detect peak position and amplitude of T waves in ECG precisely. 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