Share This Article:

Electrocardiogram Feature Extraction and Pattern Recognition Using a Novel Windowing Algorithm

Abstract Full-Text HTML XML Download Download as PDF (Size:4041KB) PP. 886-894
DOI: 10.4236/abb.2014.511103    4,128 Downloads   4,905 Views   Citations

ABSTRACT

This paper presents a Novel Windowing Algorithm for Electrocardiogram Feature Extraction and Pattern Recognition. The work presented here deals with a simple and efficient way of detecting ECG features that are P, Q, R, S and T waves. Windowing method is used to select these waves. Windows are based on varying R-R intervals. It has been tested on ECG simulator data and also on different records of the MIT-BIH arrhythmia database, producing satisfactory results. ECG timing intervals are also required for monitoring the cardiac condition of patients. Hence after feature detections ECG timing intervals like the PR interval, QRS duration, the QT interval, the QT corrected interval and Vent Rate are efficiently calculated using proposed Formulae.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Umer, M. , Bhatti, B. , Tariq, M. , Zia-ul-Hassan, M. , Khan, M. and Zaidi, T. (2014) Electrocardiogram Feature Extraction and Pattern Recognition Using a Novel Windowing Algorithm. Advances in Bioscience and Biotechnology, 5, 886-894. doi: 10.4236/abb.2014.511103.

References

[1] Razzaq, N., Butt, M., Salman, M., Ali, R., Sadiq, I., Munawar, K. and Zaidi, T. (2013) An Intelligent Adaptive Filter for Fast Tracking and Elimination of Power Line Interference from ECG Signal. 2013 IEEE 26th International Symposium on Computer-Based Medical Systems (CBMS), Porto, 20-22 June 2013, 251-256.
[2] Sagie, A., Larson, M.G., Goldberg, R.J., Bengston, J.R. and Levy, D. (1992) An Improved Method for Adjusting the QT Interval for Heart Rate (the Framingham Heart Study). American Journal of Cardiology, 70, 797-801.
http://dx.doi.org/10.1016/0002-9149(92)90562-D
[3] Bazett, H.C. (1920) An Analysis of the Time-Relations of Electrocardiograms. Heart, 7, 353-370.
[4] Mane, R.S., Cheeran, A.N., Awandekar, V.D. and Rani, P. (2013) Cardiac Arrhythmia Detection by ECG Feature Extraction. International Journal of Engineering Research and Applications, 3, 327-332.
[5] Vaneghi, F.M., Oladazimi, M., Shiman, F., Kordi, A., Safari, M.J. and Ibrahim, F. (2012) A Comparative Approach to ECG Feature Extraction Methods. Proceedings of 2012 3rd International Conference on Intelligent Systems, Modelling and Simulation (ISMS), Kota Kinabalu, 8-10 February 2012, 252-256.
http://dx.doi.org/10.1109/ISMS.2012.35
[6] Mehta, S.S. and Lingayat, N.S. (2008) Detection of P and T-Waves in Electrocardiogram. Proceedings of the World Congress on Engineering and Computer Science, San Francisco, 22-24 October 2008, 22-24.
[7] Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, P.C.H., Mark, R.G., Mietus, J.E., Moody, G.B., Peng, C.-K. and Stanley, H.E. (2000) PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation, 101, e215-e220.
http://circ.ahajournals.org/cgi/content/full/101/23/e215
[8] Razzaq, N., Butt, M., Salman, M., Ali, R., Sadiq, I., Munawar, K. and Zaidi, T. (2013) An Intelligent Adaptive Filter for Fast Tracking and Elimination of Power Line Interference from ECG Signal. 2013 IEEE 26th International Symposium on Computer-Based Medical Systems (CBMS), Porto, 20-22 June 2013, 251-256.
[9] Sagie, A., Larson, M.G., Goldberg, R.J., Bengston, J.R. and Levy, D. (1992) An Improved Method for Adjusting the QT Interval for Heart Rate (the Framingham Heart Study). American Journal of Cardiology, 70, 797-801.
http://dx.doi.org/10.1016/0002-9149(92)90562-D
[10] Bazett, H.C. (1920) An Analysis of the Time-Relations of Electrocardiograms. Heart, 7, 353-370.
[11] Mane, R.S., Cheeran, A.N., Awandekar, V.D. and Rani, P. (2013) Cardiac Arrhythmia Detection by ECG Feature Extraction. International Journal of Engineering Research and Applications, 3, 327-332.
[12] Vaneghi, F.M., Oladazimi, M., Shiman, F., Kordi, A., Safari, M.J. and Ibrahim, F. (2012) A Comparative Approach to ECG Feature Extraction Methods. Proceedings of 2012 3rd International Conference on Intelligent Systems, Modelling and Simulation (ISMS), Kota Kinabalu, 8-10 February 2012, 252-256. http://dx.doi.org/10.1109/ISMS.2012.35
[13] Mehta, S.S. and Lingayat, N.S. (2008) Detection of P and T-Waves in Electrocardiogram. Proceedings of the World Congress on Engineering and Computer Science, San Francisco, 22-24 October 2008, 22-24.
[14] Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, P.C.H., Mark, R.G., Mietus, J.E., Moody, G.B., Peng, C.-K. and Stanley, H.E. (2000) PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation, 101, e215-e220.
http://circ.ahajournals.org/cgi/content/full/101/23/e215

  
comments powered by Disqus

Copyright © 2019 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.