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Framework for Classifying Cardiac Arrhythmia

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Book cover Proceedings of 2nd International Conference on Micro-Electronics, Electromagnetics and Telecommunications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 434))

Abstract

Cardiac Arrhythmia is caused by irregular heart rhythms, it is either increased or decreased leading to irregular rhythms. The heart arrhythmia is assessed using electrocardiogram (ECG). ECG can clearly detect various types of arrhythmia and correspond to diagnosis of heart disease. There is extensive research involved in removing manual intervention in assessing the type of arrhythmia from the ECG. Arrhythmia can be classified by extracting attributes in the form of RR interval from ECG. This work proposes an approach to classify cardiac arrhythmia. A range of classifiers are proposed such as Chi-square Automatic Interaction Detector (CHAID), Random Forest (RF), and fuzzy classifier. Initially, the attributes are retrieved from the time series present in ECG data employing Discrete Cosine Transform (DCT) and then the distance among RR waves are processed. The dataset used for experimental purpose were obtained from Massachusetts Institute of Technology-Boston’s Beth Israel Hospital (MIT-BIH) arrhythmia to evaluate the performance of the method.

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Author information

Authors and Affiliations

  1. Department of ECE, Avanthi Institute Of Engineering & Technology, Vizianagaram, AP, India

    G. V. Sridhar

  2. Department of ECE, AU College of Engineering (A), Visakhapatnam, AP, India

    P. Mallikarjuna Rao

Authors
  1. G. V. Sridhar
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  2. P. Mallikarjuna Rao
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Corresponding author

Correspondence to G. V. Sridhar .

Editor information

Editors and Affiliations

  1. Deparment of Computer Science and Engineering, PVP Siddhartha Institute of Technology, Vijayawada, Andhra Pradesh, India

    Suresh Chandra Satapathy

  2. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  3. Department of ECE, Raghu Institute of Technology, Visakhapatnam, Andhra Pradesh, India

    P. Satish Rama Chowdary

  4. Department of ECE, Raghu Institute of Technology, Visakhapatnam, Andhra Pradesh, India

    V.V.S.S. Sameer Chakravarthy

  5. Department of Electronics and Telecommunications, Universitat Ramon Llull, Barcelona, Barcelona, Spain

    Jaume Anguera

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© 2018 Springer Nature Singapore Pte Ltd.

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Sridhar, G.V., Mallikarjuna Rao, P. (2018). Framework for Classifying Cardiac Arrhythmia. In: Satapathy, S., Bhateja, V., Chowdary, P., Chakravarthy, V., Anguera, J. (eds) Proceedings of 2nd International Conference on Micro-Electronics, Electromagnetics and Telecommunications. Lecture Notes in Electrical Engineering, vol 434. Springer, Singapore. https://doi.org/10.1007/978-981-10-4280-5_16

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  • DOI: https://doi.org/10.1007/978-981-10-4280-5_16

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4279-9

  • Online ISBN: 978-981-10-4280-5

  • eBook Packages: EngineeringEngineering (R0)

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