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An Automated Framework for Prediction of Falls in Cardiomyopathy People

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Abstract

Purpose In medical field, cardiomyopathy is one of the heart muscle diseases associated with blood pumping that causes heart complications like heart failures, cardiac arrest, and sudden death. According to the WHO, globally at least one in 500 is suffering from cardiomyopathy. It can be identified by symptoms such as chest pain, dizziness, syncope which causes falling. At present, in the cardiomyopathy field, issues such as poor accuracy in detection of cardiomyopathy and no emphasis on classification of cardiomyopathy types are addressed. Especially, no work is concentrated on prediction of fall due to cardiomyopathy. Hence, this work aims to propose an automated framework for prediction of fall in cardiomyopathy patients. Procedure and Conclusion This framework consists of five phases, first and second focused on improving the ECG signal quality to resolve accuracy problems. Third is to detect and classify the cardiomyopathy type as well as prediction of fall. In fourth and fifth, prediction details will be transmitted to Web application and then to personal devices.

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Conflict of Interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. School of Computer Science and Engineering, VIT University, Vellore, Tamil Nadu, India

    Pasupuleti Megana Santhoshi & Mythili Thirugnanam

Authors
  1. Pasupuleti Megana Santhoshi
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  2. Mythili Thirugnanam
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Corresponding author

Correspondence to Pasupuleti Megana Santhoshi .

Editor information

Editors and Affiliations

  1. Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore

    Balázs Gulyás

  2. Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore

    Parasuraman Padmanabhan

  3. Mar Ephraem College Of Engineering and Technology , Kanyakumari Dt, Tamil Nadu, India

    A. Lenin Fred

  4. Rajiv Gandhi Centre for Biotechnology , Thiruvananthapuram, Kerala, India

    T. R. Santhosh Kumar

  5. Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore

    Sundramurthy Kumar

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Megana Santhoshi, P., Thirugnanam, M. (2019). An Automated Framework for Prediction of Falls in Cardiomyopathy People. In: Gulyás, B., Padmanabhan, P., Fred, A., Kumar, T., Kumar, S. (eds) ICTMI 2017. Springer, Singapore. https://doi.org/10.1007/978-981-13-1477-3_1

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  • DOI: https://doi.org/10.1007/978-981-13-1477-3_1

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1476-6

  • Online ISBN: 978-981-13-1477-3

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