ECG feature extraction using principal component analysis for studying the effect of diabetes

References

• Martinez, J.P., Almeida, R., and 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
• Mahamoodabadi, S.Z., Ahamadian, A., Abolhasani, M.D., and Eslami, M., 2005, ECG feature extraction based on multiresolution wavelet transform. Proceedings of 27th Annual Conference of IEEE
   Google Scholar
• de Jesus Kozakevicius, A., Rodrigues, C.R., Nunes, R.C., and Fiillo, R.G., Adaptive ECG filtering and QRS detection using orthogonal wavelet transform
   Google Scholar
• Schuck Jr, A., and Wisback, J.O., QRS detector pre-processing using the complex wavelet transform. Proceedings of 25th Annual International Conference of IEEE
   Google Scholar
• Saxena, S.C., Kumar, V., and Hamde, S.T., 2002, Feature extraction from ECG signals using wavelet transforms for disease diagnostics. International Journal of System Science, 33, 1073–1085
   Web of Science ®Google Scholar
• Nibhanupudi, S., Youssif, R., and Purdy, C., 2004, Data specific signal denoising using wavelets with applications to ECG data. 47th International Midwest Symposium on Circuits and Systems
   Google Scholar
• Sahambi, J.S., Tandon, S.N., and Bhat, R.K., A new approach for on-line ECG characteristicspreprint
   Google Scholar
• Castro, B., Kogan, D., and Gova, A.B., 2000, ECG feature extraction using optimal mother wavelet. Institute of Electrical and Electronics Engineers
   Google Scholar
• De Chazal, P., Cellar, B.G., and Reilly, R.B., 2000, Using wavelet coefficient for the classification of electrocardiogram. Proceedings of 22nd Annual EBMS International Conference
   Google Scholar
• Kadambe, S., Murray, R., and Boudreaux-Barlets, G.F., 1999, Wavelet transform based QRS Complex detector. IEEE Transactions Biomedical Engineering, 46, 838–848
   PubMed Web of Science ®Google Scholar
• Olvera, F.E., 2006, Electrocardiogram waveform feature extraction using the matched filter
   Google Scholar
• Kaplam, D.T., 1991, Simultaneous QRS detection and feature extraction using simple matched filter basis functions. Institute of Electrical and Electronics Engineers
   Google Scholar
• Zong, W. and Jiang, D., 1998, Automated ECG rhythm analysis using fuzzy reasoning. Journal of Computers in Cardiology, IEEE, preprint69–72
   Google Scholar
• Laski, J. and Hanzel, N., 1999, A fuzzy model for ECG feature extraction. Proceedings of First Joint BMEI/EBMS Conference, IEEE
   Google Scholar
• Chowdhury, E. and Le Ludeman, 1994, Discrimination of cardiac arrhythmias using a fuzzy rule based method. Journal of Computers in Cardiology, IEEEpreprint, 549–552
   Google Scholar
• Kundu, M., Nasipuri, M., and Basu, D.K., 1998, A knowledge based approach to ECG interpretation using fuzzy logic. IEEE Transactions Systems, Man, and Cybernetics, Part B: Cybernetics, 28, 237–243
   Web of Science ®Google Scholar
• Anuradha, B. and Veera Reddy, V.C., 2008, Cardiac arrhythmia classification using fuzzy classifiers. Journal of Theoretical and Applied Information Technology, 4, 353–359
   Google Scholar
• Lascu, M. and Lascu, D., 2008, LabVIEW electrocardiogram event and beat detection. WSEAS Transactions on Computer Research, 3, 9–18
   Google Scholar
• National Instruments Developer Zone., 2008, LabVIEW for ECG signal processing
   Google Scholar
• Qin, S., Ji, Z., and Zhu, H., 2003, The ECG recording and analysis instrumentation based on virtual instrument technology and continuous wavelet transform. Proceedings of 25th IEEE Annual International Conference
   Google Scholar
• Bhyri, C., Kalpana, V., Hamde, S.T., and Wwghmare, L.M., 2009, Estimation of ECG features using LabVIEW. TECHNIA – International Journal of Computing Science and Communication Technologies, 2, 320–324
   Google Scholar
• Faezipour, M., Saeed, A., Bulusu, S.C., Nourani, M., Minn, H., and Tamil, L., 2010, A patient-adaptive profiling scheme for ECG beat classification. IEEE Transactions on Information Technology in Biomedicine, 14, 1153–1165
   PubMedGoogle Scholar
• Castells, F., Laguna, P., Sornmo, L., Bollmann, A., and Millet Roig, J., 2007, Principal component analysis in ECG signal processing. EURASIP Journal on Advances in Signal Processing, 2007, 074580
   Google Scholar
• Chawla, M.P.S., 2007, Parameterization and R-peak error estimations of ECG signals using independent component analysis. Computational and Mathematical Methods in Medicine, 8, 263–285
   Google Scholar
• Chawla, M.P.S., Verma, H.K., and Kumar, V., ECG modeling and QRS detection using principal component analysis. IET Proceedings, International Other, MEDSIP-06 (Glasgow, UK), July
   Google Scholar
• Huang, B. and Wang, Y., 2009, QRS complex detection by using the PCA and combined wavelet entropy for 12-lead ECG signal. Ninth IEEE International Conference on Computer and Information Technology (Xiamen, China), 1114 October 2009, Vol. 1preprint, pp. 246–251
   Google Scholar
• Kumar, R., Fisher, M., and Macfarlane, P.W., 2004, Diabetes and the QT internal: Time for debate. The British Journal of Diabetes and Vascular Disease, 4, 146–150
   Google Scholar
• Okin, P.M., Devereux, R.B., Lee, E.T., Galloway, J.M., and Howard, B.V., 2004, Electrocardiographic repolarization complexity and abnormality predict all-cause and cardiovascular mortality in diabetes. Diabetes Journal, 53, 434–440
   PubMed Web of Science ®Google Scholar
• Stern, S. and Sclarowsky, S., 2009, The ECG in diabetes mellitus. Circulation, 120, 1633–1636
   Google Scholar
• Yazici, M., Ozdemir, K., Altunkeser, B.B., Kayrak, M., Duzenli, A., Vatankulu, M.A., Soylu, M.A., and Ulgen, M.S., 2007, The effect of diabetes mellitus on the p-wave dispersion. Japanese Circulation Society
   Google Scholar
• Farina, P.V.R., Turiel, J.P., Pagan-Buzo, F.J., Sarmiento, E.G., Lopez, A.H., and Rodriguez-Guerrero, C.D., 2010, QTc analysis and comparison in pre-diabetic patients. Computers in Cardiology
   Google Scholar
• Medical News Today, “What is diabetes? What causes diabetes?” Medical News Today
   Google Scholar
• National Diabetes Statistics, 2011, National diabetes information clearing house
   Google Scholar
• Jacobson, M.L., 2003, Non-invasive clinical screening of diabetes and coronary heart disease. Proceedings of 4th Annual IEEE Conference of Information Technology Applications in Biomedicine
   Google Scholar
• Saudek, C., 2002, President American diabetes association and professor of medicine at John Hopkins university school of medicine. Diabetes. US news and world report
   Google Scholar
• Smalley, B., 2001, Diabetes will strike half of UAE population in 25 years. Gulf news (A1 Nisr publishing)
   Google Scholar
• Diabetes mellitus – Wikipedia
   Google Scholar
• Leong, K., 2009, Diabetics: Do you need an ECG? Healthmad
   Google Scholar
• Voulgari, C., Tantolouris, N., and Stefanadis, C., 2011, The ECG vertigo in Diabetes and Cardiac Autonomic Neuropathy. Experimental Diabetes Research
   Google Scholar
• Gonzalez, R., Fernandez, R., and Ria del Carmen Raola, M., 2000, Real-time QT interval measurement. Proceedings of the 22nd Annual EMBS International Conference, July
   Google Scholar
• Afsar, F.A., Riaz, M.S., and Arif, M., 2009, A comparison of baseline removal algorithms for electrocardiogram (ECG) based automated diagnosis of coronary heart diseases. Institute of Electrical and Electronics Engineers
   Google Scholar