Abstract
In the present paper, we propose a soft computing diagnostic intelligent system that classifies ECG beats in different phases and enables us to identify the status of cardiac health normalities and abnormalities as per available ECG graphs. In order to design and develop an intelligent computing system, we have used some important parts of ECGs as fuzzy input variables for our diagnostic system, i.e. hexaxial system and R–R interval from different concerned patients’ ECG graph, which are useful to detect cardiac health status. Then, with the consultation of medical experts, we have developed a fuzzy rule base system with the input variables, which, in turn, are helpful in developing utility matrix. Using these fuzzy input variables and utility matrix, the diagnostic system detects various cardiac statuse of the concerned patient, which has been verified with the help of cardiac experts. The intelligent system will be very helpful to society.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Adeli, A., Neshat, M.: A fuzzy expert system for heart disease diagnosis. In: Proceedings of the International Multi Conference of Engineers and Computer Scientists, pp. 134–139 (2010)
Andreao, R.V., Dorizzi, B., Boudy, J.: ECG Signal Analysis through Hidden Markov Models. IEEE Trans. Biomed. Eng. 53(8), 1541–1549 (2006)
Bellman, R.E., Zadeh, L.A.: Decision making in a fuzzy environment. Manage. Sci. 17(4), B141–B164 (1970)
Degani, R.: Computerized electrocardiogram diagnosis: fuzzy approach. Methods Inf. Med. 31, 225–233 (1992)
Hu, Y.H., Palreddy, S., Tompkins, W.J.: Patient adaptable ECG beat classifier using a mixture of experts approach. IEEE Trans. Biomed. Eng. 44(9), 891–897 (1997)
Jain, R.: Decision making in the presence of fuzzy variables. IEEE Trans. Syst. Man Cybern. 6(10), 698–703 (1967)
Jena, R.K., et al.: Soft computing methodologies in bioinformatics. Eur. J. Sci. Res. 26, 189–203 (2004)
Luthra, A.: ECG Made Easy, 3rd edn, Jaypee Brothers, New Delhi(2007)
Klire, G.J., Yuan, B.: Fuzzy Sets and Fuzzy Logic: Theory and Applications, PHI Learning Private Limited, New Delhi (2009)
Osowski, S., Linh, T.H.: ECG beat recognition using fuzzy hybrid neural network. IEEE Trans. Biomed. Eng. 48(11), 1265–1271 (2001)
Pandey, D., Mahajan, V., Srivastava, P.: Rule based system for cardiac analysis. Natl. Acad. Sci. Lett. 29(7 & 8), 299–309 (2006)
Srivastava, P., Srivastava, A.: A note on soft computing approach for cardiac analysis. J. Basic. Appl. Sci. Res. 2(1), 376–385 (2012)
Srivastava, P., Srivastava, A.: Spectrum of soft computing risk assessment scheme for hypertension. Int. J. Comput. Appl. (0975–8887) 44(17), 23–30 (2012)
Srivastava, P., Sharma, N.: A spectrum of soft computing model for medical diagnosis. Appl. Math. Inf. Sci. 8(3), 1225–1230 (2014)
Srivastava, P., Sharma, N., Singh, R.: Soft computing diagnostic system for diabetes. Int. J. Comput. Appl. (0975–888) 47(18), 22–27 (2012)
Übeyli, E.D.: Combining recurrent neural networks with eigen vector methods for classification of ECG beats. Dig. Signal Process. 19(2) (2009)
Verma, P.: A soft computing approach for classification scheme of ECG beats, M.Sc. thesis Environment Science Allahabad University (2009)
Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)
Zadeh, L. A.: On fuzzy algorithms, Memo No. ERL-M325, Electronics Research Laboratory, University of California (1972)
Zadeh, L.A.: Outline of a new approach to the analysis of complex systems and decision process. IEEE Trans. Syst. Man Cybern. SMC 3(1), 28–44 (1973)
Acknowledgements
We sincerely acknowledge Dr. Geeta Shukla, cardiologist, Nazarth Hospital, Allahabad and Dr. R.P. Singh, Prabha Medical Center, Shantipuram, Phaphamau for providing different ECGs data and regarding their useful suggestions and discussion on the validation of results in the present article.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Srivastava, P., Sharma, N. (2022). Intelligent System for ECG Beat Classification. In: Srivastava, P., Thakur, S.S., Oros, G.I., AlJarrah, A.A., Laohakosol, V. (eds) Mathematical, Computational Intelligence and Engineering Approaches for Tourism, Agriculture and Healthcare . Lecture Notes in Networks and Systems, vol 214. Springer, Singapore. https://doi.org/10.1007/978-981-16-3807-7_8
Download citation
DOI: https://doi.org/10.1007/978-981-16-3807-7_8
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-3806-0
Online ISBN: 978-981-16-3807-7
eBook Packages: EngineeringEngineering (R0)