Backpropagation Based Analysis of Digitized Electrocardiogram

Backpropagation Based Analysis of Digitized Electrocardiogram

Authors

  • Shivali S Government College of Engineering and Technology Jammu
  • Sameru Sharma Government College of Engineering and Technology Jammu
  • Ajay Abrol Government College of Engineering and Technology

Keywords:

Digitalization, Artificial Intelligence, ECG

Abstract

In this work, digitized ECG are downloaded from Physionet, features like time intervals and amplitudes are recorded and used in analysis & classification of data. A total of 95 beats are used in this study from MITBIH arrhythmia. 27 beats are used for training and 15 beats are used for training. A sensitivity of 72%, specificity of 98.61% and accuracy of 92.51% has been achieved which is comparable to other studies.  The network used has 10-20-7 configuration.

References

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Meghashree S J1, Shankar B B2, Praveen J3, Raghavendra Rao, “ ECG Feature Extraction Analysis System for Arrythmia Detection-A Review” international journal of innovative research in electrical, electronics, instrumentation and control engineering Vol. 3, Issue 3, March 2015 pp 107-109

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Durgesh Kumar Ojha, Monica Subashini, “Analysis of Electrocardiograph (ECG) Signal for the Detection of Abnormalities Using MATLAB” International Journal of Medical, Health, Biomedical and Pharmaceutical Engineering Vol:8, No:2, 2014, pp .120-123.

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Published

2023-12-31

How to Cite

S, S., Sharma, S., & Abrol, A. (2023). Backpropagation Based Analysis of Digitized Electrocardiogram. IARS’ Knowledge Planet, (978-1-922642-02-8). Retrieved from https://jconsortium.com/index.php/iarsbookplanet/article/view/774

Issue

No. 978-1-922642-02-8 (2023): 9th NCEEITET

Section

Book Chapter

License

Copyright (c) 2023 Shivali S, Sameru Sharma, Ajay Abrol

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Author(s) hold complete right on the content of this article.