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International Conference on Intelligent Information Technologies

ICIIT 2018: Advances in Data Science pp 130–140Cite as

Linear and Nonlinear Analysis of Cardiac and Diabetic Subjects

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 941))

Abstract

Cardiac health issues are severe and cause maximum death according to the survey done by “World Health Organization” (WHO). Cardiac diseases are caused due to family history, living style, diabetes, etc. Diagnosis of cardiac health prior to pathological conditions is highly important. Heart Rate Variability (HRV) is the technique used to study the cardiac abnormalities, which are related to fluctuation in the sympathetic and parasympathetic activities. In this paper, we compare the time domain, frequency domain and nonlinear parameters of heart rate variability for 73 subjects. Our results show that HRV parameters are high for normal subjects compared to diabetic subjects and lowest for cardiac subjects. The results are validated by diagnosis done through clinical processes. Thus non-invasive ECG and HRV techniques help to diagnose the subject before it causes the cardiac arrest.

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Author information

Authors and Affiliations

  1. Electronics Engineering Department, A.C. Patil College of Engineering, Navi Mumbai, India

    Ulka Shirole

  2. Electronics and Telecommunication Department, MPSTME, NMIMS Deemed to be University, Mumbai, India

    Manjusha Joshi

  3. B and J super specialty hospital, Kamothe, Navi Mumbai, India

    Pritish Bagul

Authors
  1. Ulka Shirole
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  2. Manjusha Joshi
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  3. Pritish Bagul
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Corresponding author

Correspondence to Ulka Shirole .

Editor information

Editors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, PA, USA

    Leman Akoglu

  2. University of Southern California, Marina Del Rey, CA, USA

    Emilio Ferrara

  3. CEG, Anna University, Chennai, India

    Mallayya Deivamani

  4. Northeastern University at Silicon Valley, San Jose, CA, USA

    Ricardo Baeza-Yates

  5. Anna University, Chennai, India

    Palanisamy Yogesh

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© 2019 Springer Nature Singapore Pte Ltd.

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Shirole, U., Joshi, M., Bagul, P. (2019). Linear and Nonlinear Analysis of Cardiac and Diabetic Subjects. In: Akoglu, L., Ferrara, E., Deivamani, M., Baeza-Yates, R., Yogesh, P. (eds) Advances in Data Science. ICIIT 2018. Communications in Computer and Information Science, vol 941. Springer, Singapore. https://doi.org/10.1007/978-981-13-3582-2_10

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  • DOI: https://doi.org/10.1007/978-981-13-3582-2_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-3581-5

  • Online ISBN: 978-981-13-3582-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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