CAD DETECTION USING NEURAL NETWORK FUSION OF THE 12 LEAD STRESS ECG SYSTEM

Galal M. BinMakhashen, Samer M. A. Arafat, and Mary L. Dohrmann

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References

  1. [1] G. Diamond and J. Forester, "Analysis of Probability as an aid in the clinical diagnosis of Coronary-Artery Disease," New England Journal of Medicine, vol. 300, pp. 1350-1358, 1979.
  2. [2] B. Vuksanovic and M. Alhamdi, “ECG based system for arrhythmia detection and patient identification,” in Proceedings of the ITI 2013 35th International Conference on Information Technology Interfaces (ITI), 2013, pp. 315–320.
  3. [3] C. Ye, B. V. K. Vijaya Kumar, and M. T. Coimbra, “Combining general multi-class and specific two-class classifiers for improved customized ECG heartbeat classification,” in 2012 21st International Conference on Pattern Recognition (ICPR), 2012, pp. 2428–2431.
  4. [4] A. Li, S. Wang, H. Zheng, L. Ji, and J. Wu, “A novel abnormal ECG beats detection method,” in 2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE), 2010, vol. 1, pp. 47–51.
  5. [5] J. Malmivuo and R. Plonsey, Bioelectromagnetism Principles and Applications of Bioelectric and Biomagnetic Fields. Oxford University Press, 1995.
  6. [6] J. A. Scherer and J. L. Willems, “Evaluation of 12lead ECG synthesis using analysis measurements in 240 patients,” in Proceedings of Computers in Cardiology 1992, 1992, pp. 91–94.
  7. [7] I. Tomasic and R. Trobec, “Electrocardiographic systems with reduced numbers of leads synthesis of the 12-lead ECG,” Biomed. Eng. IEEE Rev. In, vol. Early Access Online, 2013.
  8. [8] H. Atoui, J. Fayn, and P. Rubel, “A neural network approach for patient-specific 12-lead ECG synthesis in patient monitoring environments,” in Computers in Cardiology, 2004, 2004, pp. 161–164.
  9. [9] F. Agrafioti and D. Hatzinakos, “Fusion of ECG sources for human identification,” in 3rd International Symposium on Communications, Control and Signal Processing, 2008. ISCCSP 2008, 2008, pp. 1542–1547.
  10. [10]B. R. Greene, G. B. Boylan, R. B. Reilly, P. de Chazal, and S. Connolly, “Combination of EEG and ECG for improved automatic neonatal seizure detection,” Clin. Neurophysiol., vol. 118, no. 6, pp. 1348–1359, Jun. 2007.
  11. [11]W. Deburchgraeve, P. J. Cherian, M. De Vos, R. M. Swarte, J. H. Blok, G. H. Visser, P. Govaert, and S. Van Huffel, “Automated neonatal seizure detection mimicking a human observer reading EEG,” Clin. Neurophysiol., vol. 119, no. 11, pp. 2447–2454, Nov. 2008.
  12. [12]A. Ross, N. Karthik, and A. K. Jain, Handbook of Multibiometrics, vol. Vol. 6. Springer Berlin Heidelberg, 2006.
  13. [13]M. Arif, I. A. Malagore, and F. A. Afsar, “Automatic Detection and Localization of Myocardial Infarction Using Back Propagation Neural Networks,” in 2010 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE), 2010, pp. 1–4.
  14. [14]E.-S. M. El-Alfy and G. M. BinMakhashen, “Improved Personal Identification Using Face and Hand Geometry Fusion and Support Vector Machines,” in Networked Digital Technologies. Springer Berlin Heidelberg, 2012, pp. 253–261.
  15. [15]V. A. Allen and J. Belina, “ECG data compression using the discrete cosine transform (DCT),” in Proceedings of Computers in Cardiology 1992, 1992, pp. 687–690.
  16. [16]R. J. Martis, U. R. Acharya, and L. C. Min, “ECG beat classification using PCA, LDA, ICA and Discrete Wavelet Transform,” Biomed. Signal Process. Control, vol. 8, no. 5, pp. 437–448, Sep. 2013.
  17. [17] P. Gokhale, “ECG Signal Denoising using Discrete Wavelet Transform for removal of 50Hz PLI noise, "Int. J. Emerg. Technol. Adv. Eng., vol. 2, no. 5, pp. 81 85, 2012.
  18. [18] S. Arafat and M. Skubic, “Modeling Fuzziness Measures for Best Wavelet Selection,” IEEE Transactions on Fuzzy Systems, October 2008.
  19. [19]J. Bushra, L. Olivier, F. Eric, and B. Ouadi, “Detection of QRS complex in ECG signal based on classification approach,” in 2010 17th IEEE International Conference on Image Processing (ICIP), 2010, pp. 345– 348.

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