References
- Sornmo, L., Laguna, P., 2005, Bioelectrical signal processing in cardiac and neurological applications (Amsterdam: Elsevier Academic Press).
- Acharya, U.R., Suri, J.S., Spaan, J.A.E., Krishnan, S.M., 2007, Advances in cardiac signal processing (Springer-Verlag, Berlin, Heidelberg).
- Benitez, D., Gaydecki, P.A., Zaidi, A., Fitzpatrick, A.P., 2001, The use of the Hilbert transform in ECG signal analysis. Computers in Biology and Medicine, 31, 399–406.
- Bolton, R.J., Westphal, L.C., 1985, ECG display and QRS detection using the Hilbert Transform. In: Ripley, K.L., editor. Computers in cardiology (Washington, DC: IEEE Computer Society), p 463–466.
- Bolton, R.J., Westphal, L.C., 1981, Hilbert transform processing of ECG’s. 1981 IREECON International Convention Digest (Melbourne: IREE). pp. 281–283.
- Bolton, R.J., Westphal, L.C., 1984, On the use of the Hilbert Transform for ECG waveform processing. Computers in cardiology (Silver Spring, MD: IEEE Computer Society). pp. 533–536.
- Bolton, R.J., Westphal, L.C., 1981, Preliminary results in display and abnormality of Hilbert Transformed e.c.g.s. Medical & Biological Engineering & Computing, 19, 377–384.
- Kadamb, S., Murray, R., Bartels, G.F.B., 1999, Wavelet transformbased QRS complex detector. IEEE Transactions on Biomedical Engineering, 46, 838–848.
- Ji, Z., Qin, S., Peng, C., 2006, Electrocardiographic signal feature extraction and its instrument development based on continuous wavelet transform. Journal of Biomedical Engineering, 23, 1186–1190.
- Li, C., Zheng, C., Tai, C., 1995, Detection of ECG characteristic points using wavelet transforms. IEEE Transactions on Biomedical Engineering, 42, 21–28.
- Mahmoodabadi, S., Ahmadian, A., Bolhasani, A.M., Eslami, M., Bidgoli, J., 2005, ECG feature extractionbased on multiresolution wavelet transform. Conference Proceedings - IEEE Engineering Medicine & Biology Society, 4, 3902–3905.
- Matsuyama, A., Jonkman, M., Boer, F.D.E., 2007, Improved ECG signal analysis using wavelet and feature extraction. Methods of Information in Medicine, 46, 227–230.
- Sahambi, J.S., Tandon, N., Bhatt, R.K.P., 1997, Using wavelet transforms for ECG characterization: An online digital signal processing system. IEEE Engineering in Medicine and Biology Magazine, 16, 77–83.
- Wong, S., Francisco, N.G., Mora, F., Passariello, G., Almeida, D., 1998, QT Interval Time Frequency Analysis using Haar Wavelet. Computers in Cardiology, 25, 405–408.
- Coast, D.A., Stem, R.M., Cano, G.G., Briller, S.A., 1990, An approach to cardiac arrhythmia analysis using Hidden Markov Models. IEEE Transactions in Biomedical Engineering, 37, 826–836.
- Koski, A., 1996, Modelling ECG signals with Hidden Markov Models. Artificial Intelligence in Medicine, 8, 453–471.
- Mitra, S., Mitra, M., Chaudhuri, B.B., 2009, Pattern defined heuristic rules and directional histogram based online ECG parameter extraction. Measurement, 42, 150–156.
- Shahram, M., Nayebi, K., 2001, ECG beat classification based on a cross-distance analysis. International Symposium on Signal Processing and its Applications, Malaysia, pp. 234–237.
- Laguna, P., Jane, R., Olmos, S., Thakor, N.V., Rix, H., Caminal, P., 1996, Adaptive estimation of QRS complex wave features of ECG signal by the Hermite model. Medical & Biological Engineering & Computing, 34, 58–68.
- Mehta, S.S., Sexana, S.C., Verma, H.K., 1996, Computer-aided interpretation of ECG for diagnostics. International Journal of System Science, 27, 43–58.
- Yu, X.Y., Xu, X.X., 2000, QRS detection based on neural-network. Journal of Biomedical Engineering, 17, 59–62.
- Strintzis, M.G., Stalidis, G., Magnisalis, X., Maglaveras, N., 1992, Use of neural networks for electrocardiogram (ECG) feature extraction, recognition and classification. Neural Network World, 3, 477–484.
- Botter, E.D.A., Nascimento, C.L., Yoneyama, T., 2001, A neural network with asymmetric basis functions for feature extraction of ECG P waves. IEEE Transactions on Neural Networks, 12, 1252–1255.
- Engin, M., 2004, ECG beat classification using neuro-fuzzy network. Pattern Recognition Letters, 25, 1715–1722.
- Israel, S.A., Irvine, J.M., Cheng, A., Wiederbold, M.D., Wiederhold, B.K., 2005, ECG to identify individuals. Pattern Recognition, 38, 133–142.
- Arzeno, N.M., Poon, C.S., Deng, Z.D., 2006, Quantitative analysis of QRS detection algorithms based on first derivative of the ECG. In: Proceedings of 28th IEEE EMBS annual international conference, New York, p 1788–1791.
- Paoletti, M., Marchesi, C., 2006, Discovering dangerous patterns in long-term ambulatory ECG recordings using a fast QRS detection algorithm and explorative data analysis. Computer Methods and Programs in Biomedicine, 82, 20–30.
- Lin, K.P., Chang, W.H., 1989, QRS feature extraction using linear prediction. IEEE Transactions in Biomedical Engineering, 36, 1050–1055.
- Poli, R., Cagnoni, S., Valli, G., 1995, Genetic design of optimum linear and nonlinear QRS detectors. IEEE Transactions in Biomedical Engineering, 42, 1137–1141.
- Mitra, S., Mitra, M., Chaudhuri, B.B., 2006, A Rough-Set-Based Inference Engine for ECG Classification. IEEE Transactions on Instrumentation and Measurement, 55, 2198–2206.
- Jovic, A., Bogunovic, N., 2007, Feature Extraction for ECG Time- Series Mining based on Chaos Theory. Proceedings of 29th International Conference on Information Technology Interfaces, 25–28 June 2007, Cavtat/Dubrovnik, Croatia, p 63–68.
- Ubeyli Derya, E., 2008, Feature extraction for analysis of ECG signals. Engineering in Medicine and Biology Society, EMBS 2008. 30th Annual International Conference of the IEEE, Vancouver, Canada, pp. 1080–1083.
- Xu, X., Liu, Y., 2004, ECG QRS Complex Detection Using Slope Vector Waveform (SVW) Algorithm. Proceedings of the 26th Annual International Conference of the IEEE EMBS, San Francisco, CA, pp. 3597–3600.
- Analogic. Universal waveform analyzer, Application Note No. 301 ( Advanced Math) (Analogic Ltd, Massachusetts, United States). pp. 1301-1–1301-5.
- Mehta, S.S., Lingayat, N.S., 2009, Identification of QRS complexes in 12-lead electrocardiogram. Expert Systems with Applications, 36, 820–828.
- Mukhopadhyay, S.K., Mitra, M., Mitra, S., 2011, A lossless ECG data compression technique using ASCII character encoding. Computers and Electrical Engineering, 37, 486–497.
- Gritzali, F., 1988, Towards a generalized scheme for QRS Detection in ECG waveforms. Signal Processing, 15, 183–192.
- Kyrkos, A., Giakoumakis, E.A., Carayannis, G., 1988, QRS detection through time recursive prediction technique. Signal Processing, 15, 429–436.
- Trahanias, P., Skordalalkis, E., 1989, Bottom up approach to the ECG pattern-recognition problem. Medical and Biological Engineering and Computing, 27, 221–229.
- Trahanias, P.E., 1993, An approach to QRS complex detection using mathematical morphology. IEEE Transactions on Biomedical Engineering, 40, 201–205.
- Jafari, P., Fard, M., Moradi, M.H., Tajvidi, M.R., 2008, A novel approach in R peak detection using Hybrid Complex Wavelet (HCW). International Journal of Cardiology, 124, 250–253.
- Ghaffari, A., Golbayani, H., Ghasemi, M., 2008, A new mathematical based QRS detector using continuous wavelet transform. Computers and Electrical Engineering, 34, 81–91.
- Li, C., Zheng, C., Tai, C., 1995, Detection of ECG characteristic points using wavelet transforms. IEEE Transactions in Biomedical Engineering, 42, 21–28.
- Martinez, J.P., Almeida, R., Olmos, S., Rocha, A.P., Laguna, P., 2004, A wavelet based ECG delineator: evaluation on standard database. IEEE Transactions in Biomedical Engineering, 51, 570–581.
- Adnane, M., Jiang, Z., Choi, S., 2009, Development of QRS detection algorithm designed for wearable cardiorespiratory system. Computer Methods and Programs in Biomedicine, 93, 20–31.