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Research Article

ECG beat classification using empirical mode decomposition and mixture of features

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Pages 652-661 | Received 03 Feb 2017, Accepted 16 Oct 2017, Published online: 07 Nov 2017

References

  • Poornachandra S, Kumaravel N. Hyper-trim shrinkage for de-noising of ECG signal. Digit Signal Process. 2005;15:317–327.
  • Singh BN, Tiwari AK. Optimal selection of wavelet basis function applied to ECG signal de-noising. Digit Signal Process. 2006;16:275–287.
  • Kumari R, Sadasivam V. De-noising and baseline wandering removal of electrocardiogram using double density discrete wavelet. Int J Wavelets Multiresolut Inf Process. 2007;5:399–415.
  • Kim T, Ko D, Vasilakos T, et al. Proceedings of international conferences on computer applications for communication, networking, and digital contents. 2012;343–345.
  • Sahoo SK, Biswal P, Das T, et al. De-noising of ECG signal and QRS detection using Hilbert transform and adaptive thresholding. Procedia Tech. 2016;25:68–75.
  • Chen S, Chen H, Chan H. A real-time QRS detection method based on moving-averaging incorporating with wavelet de-noising. Comput Methods Programs Biomed. 2006;82:187–195.
  • Karimipour A, Homaeinezhad MR. Real-time electrocardiogram P-QRS-T detection–delineation algorithm based on quality-supported analysis of characteristic templates. Comput Biol Med. 2014;52:153–165.
  • Jenkal W, Latif R, Toumanari A, et al. An efficient algorithm of ECG signal de-noising using the adaptive dual threshold filter and the discrete wavelet transform. Biocybern Biomed Eng. 2016;36:499–508.
  • Kabir MA, Shahnaz C. De-noising of ECG signals based on noise reduction algorithms in EMD and wavelet domains. Biomed. Signal Process Control. 2012;7:481–489.
  • Su L, Zhao G. De-Noising of ECG signal using translation-invariant wavelet de-noising method with improved thresholding. Conf Proc IEEE Eng Med Biol Soc. 2005;5946–5949.
  • Awal MA, Mostafa SS, Ahmada M, et al. An adaptive level dependent wavelet thresholding for ECG de-noising. Biocybern Biomed Eng. 2014;34:238–249.
  • Gupta P, Sharma K, Joshi S. Baseline wander removal of electrocardiogram signals using multivibrate empirical mode decomposition. Healthc Technol Lett. 2015;2:164–166.
  • Nimunkar A, Tompkins W. R-peak Detection and signal averaging for simulated stress ECG using EMD. Conf Proc IEEE Eng Med Biol Soc. 2007;1261–1264.
  • Rabbani H, Mahjoobi M, Farahabadi E, et al. R-peak detection in electrocardiogram signal based on an optimal combination of wavelet transform, Hilbert transform, and adaptive thresholding. J Med Signals Sens. 2011;1:91–98.
  • Slimane Z, Nait-Ali A. QRS complex detection using empirical mode decomposition. Digit Signal Process. 2010;20:1221–1228.
  • Luz EJS, Schwartz WR, Chavez GC, et al. ECG-based heartbeat classification for arrhythmia detection: a survey. Comput Methods Programs Biomed. 2016;127:144–164.
  • Mohamed B, Issam A, Mohamed A, et al. ECG image classification in real time based on the Haar-like features and artificial neural networks. Procedia Comput Sci. 2015;73:32–39.
  • Hu YH, Palreddy S, Tompkins WJ. A patient-adaptable ECG beat classifier using a mixture of experts approach. IEEE Trans Biomed Eng. 1997;44:891–900.
  • Velasco M, Weng B, Barner KE. ECG signal denoising and baseline wander correction based on the empirical mode decomposition. Comput Biol Med. 2008;38:1–13.
  • Moody GB, Mark GR. The impact of the MIT-BIH arrhythmia database. IEEE Eng Med Biol Mag. 2001;20:45–50.
  • Mallat S. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Machine Intell. 1989;2:674–693.
  • Pal S, Mitra M. Empirical mode decomposition based ECG enhancement and QRS detection. Comput Biol Med. 2012;42:83–92.
  • Rodriguez R, Mexicano A, Billa J, et al. Feature extraction of electrocardiogram signals by applying adaptive threshold and principal component analysis. J Appl Res Tech. 2015;13:261–269.
  • Banerjee S, Gupta R, Mitra M. Delineation of ECG characteristic features using multiresolution wavelet analysis method. Measurement. 2012;45:474–487.
  • Duda RO, Hart PE, Stork DG. Pattern classification. 2nd ed. New York: Wiley; 2001.
  • Wang JS, Chiang WC, Hsu YL, et al. ECG arrhythmia classification using a probabilistic neural network with a feature reduction method. Neurocomputing. 2013;116:38–45.
  • Martis RJ, Acharya UR, Min LC. ECG beat classification using PCA, LDA, ICA and discrete wavelet transform. Biomed. Signal Process Control. 2013;8:437–448.
  • Yu S, Chen Y. Electrocardiogram beat classification based on wavelet transformation and probabilistic neural network. Pattern Recognit Lett. 2007;28:1142–1150.
  • Banerjee S, Mitra M. ECG beat classification based on discrete wavelet transformation and nearest neighbour classifier. J Med Eng Technol. 2013;37:264–272.
  • Afkhami RG, Azarnia G, Tinati MA. Cardiac arrhythmia classification using statistical and mixture modelling features of ECG signals. Pattern Recognit Lett. 2016;70:45–51.
  • Elhaj FA, Salima N, Harris AR, et al. Arrhythmia recognition and classification using combined linear and nonlinear features of ECG signals. Comput Methods Programs Biomed. 2016;127:52–63.
  • Chazal P, Reilly RB. A patient-adapting heartbeat classifier using ECG morphology and heartbeat interval features. IEEE Trans Biomed Eng. 2006;53:2535–2543.
  • Martis RJ, Acharya UR, Mandana KM, et al. Application of principal component analysis to ECG signals for automated diagnosis of cardiac health. Expert Syst Appl. 2012;39:11792–11800.
  • Shadmand S, Mashoufi B. A new personalized ECG signal classification algorithm using block-based neural network and particle swarm optimization. Biomed. Signal Process Control. 2016;25:12–23.

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