K-nearest neighbour-based algorithm for P- and T-waves detection and delineation

References

• Li, C., Zheng, C., and Tai, C., 1995, Detection of ECG characteristic points using wavelet transforms. IEEE Transactions on Biomedical Engineering, 42, 21–28
   PubMed Web of Science ®Google Scholar
• Martinez, J.P., Olmos, S., and Laguna, P., 2000, Evaluation of a wavelet-based ECG waveform detector on the QT database. Computers in Cardiology, 27, 81–84
   Google Scholar
• Martinez, J.P., Almeida, R.S., Olmos S., Rocha, A.P., and Laguna, P., 2004, A Wavelet-based ECG delineator: Evaluation on standard databases. IEEE Transactions on Biomedical Engineering, 51, 570–581
   PubMed Web of Science ®Google Scholar
• Goutas, A., Ferdi, Y., Herbeuval, J.-P., Boudraa, M., and Boucheham, B., 2005, Digital fractional order differentiation-based algorithm for P and T-waves detection and delineation. ITBM-RBM, 26, 127–132
   Google Scholar
• Sun, Y., Chan, K.L., and Krishnan, S.M., 2005, Characteristic wave detection in ECG signals using morphological transform. BMC Cardiovascular Disorders, 5, 28–34
   Google Scholar
• Andreao, R.V., Dorizzi, B., and Boudy, J., 2006, ECG signal analysis through hidden Markov Models. IEEE Transactions on Biomedical Engineering, 53, 1541–1549
   PubMedGoogle Scholar
• Mehta, S.S., and Lingayat, N.S., 2007, Comparative study of QRS detection in single lead and 12-lead ECG based on entropy and combined entropy criteria using support vector machine. Journal of Theoretical and Applied Information Technology, 3, 8–18
   Google Scholar
• Chouhan, V.S., and Mehta, S.S., 2008, Threshold-based detection of P and T wave in ECG using new feature signal. International Journal of Computer Science and Network Security, 8, 144–152
   Google Scholar
• Arzeno, N.M., Deng, Z.-D., and Poon, C.-S., 2008, Analysis of first-derivative based QRS detection algorithms. IEEE Transactions on Biomedical Engineering, 55, 478–484
   PubMed Web of Science ®Google Scholar
• Mehta, S.S., and Lingayat, N.S., 2009, Application of support vector machine for the detection of P- and T-waves in 12-lead electrocardiogram. Computer methods and programs in Biomedicine, 93, 46–60
   PubMed Web of Science ®Google Scholar
• Dumont, J., Hernandez, A.I., and Carrault, G., 2010, Improving ECG beat delineation with an evolutionary optimization process. IEEE Transactions on Biomedical Engineering, 57, 607–615
   PubMedGoogle Scholar
• Lin, C., Mailhes, C., and Tourneret, J.-Y., 2010, P- and T-Wave delineation in ECG signals using a Bayesian Approach and a partially collapsed Gibbs Sampler. IEEE Transactions on Biomedical Engineering, 57, 2840–2849
   PubMed Web of Science ®Google Scholar
• Dasarathy, B.V., 1990, Nearest Neighbor (NN) norms: NN Pattern Classification Techniques (Los Alamitos: IEEE Computer Society Press)
   Google Scholar
• Yazdani, A., Ebrahimi, T., and Hoffmann, U., 2009, Classification of EEG signals using Dempster Shafer Theory and a K-Nearest Neighbor Classifier. Proceedings of the 4th International IEEE EMBS Conference on Neural Engineering, 1, pp. 327–330
   Google Scholar
• Zheng, G., and Cao, G., 2008, A modified K-NN algorithm for holter waveform classification based on kernel function. IEEE Computer Society-Fifth International Conference on Fuzzy Systems and Knowledge Discovery (Shandong), pp. 343–346
   Google Scholar
• Alkhateeb, J.H., Khelifi, F., Jiang, J., and Ipson, S.S., 2009, A new approach for off-line handwritten arabic word recognition using KNN Classifier. IEEE International Conference on Signal and Image Processing Applications (Malaysia), pp. 191–194
   Google Scholar
• Fix, E., and Hodges, J.L., 1951, Discriminatory analysis, nonparametric discrimination: Consistency properties. Technical Report 4 (Randolph Field, TX: USAF School of Aviation Medicine)
   Google Scholar
• Saini, I., Singh, D., and Khosla, A., 2013, QRS detection using K-Nearest neighbor algorithm (KNN) and evaluation on standard ECG databases. Journal of Advanced Research, 4, 331–344
   PubMedGoogle Scholar
• Pan, J., and Tompkins, W.J., 1985, A real time QRS detection algorithm. IEEE Transactions on Biomedical Engineering, 32, 230–236
   PubMed Web of Science ®Google Scholar
• Willems, J.L., 1988, The CSE Multilead atlas manual-measurement results dataset-3 (Belgium: ACCO)
   Google Scholar
• Laguna, P., Jane, R., and Caminal, P., 1994, Automatic detection of wave boundaries in multilead ECG signals: Validation with CSE database. Computers and Biomedical Research, 27, 45–60
   PubMedGoogle Scholar
• de Chazal, P., and Celler, B., 1996, Automatic measurement of the QRS onset and offset in individual ECG leads. Presented at the 18th Annual International Conference IEEE Engineering in Medicine and Biology Society (Amsterdam, The Netherlands)
   Google Scholar
• Sahambi, J.S., Tandon, S.N., and Bhatt, R.K.P., 1997, Using wavelet transforms for ECG characterization - An on-line digital signal processing system. IEEE Engineering in Medicine and Biology, 16, 77–83
   PubMed Web of Science ®Google Scholar
• Willems, J.L., 1985, Recommendations for measurement standards in quantitative electrocardiography. European Heart Journal, 6, 815–825
   PubMed Web of Science ®Google Scholar
• Yanowitz, F.G., 2012, Introduction to ECG interpretation V8.0, Intermountain Healthcare
   Google Scholar
• Jane, R., Blasi, A., Garcia, J., and Laguna, P., 1997, Evaluation of an automatic detector of waveforms limits in holter ECG with the QT database. Computers in Cardiology (Los Alamitos, CA: IEEE Computer Society Press). pp. 295–298
   Google Scholar