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Extraction of ECG Significant Features for Remote CVD Monitoring

  • V. Naresh
  • Amit AcharyyaEmail author
Chapter
Part of the Series in BioEngineering book series (SERBIOENG)

Abstract

Remote healthcare monitoring for Cardiovascular Diseases (CVD) in the present lifestyle is of the utmost importance throughout the world because of high mortality rate, around 30% of deaths all over the world are due to the CVD as per the World Health Organization (WHO) statistics. With the advancement of medical industry and huge growth in IoT technology is gradually making the remote CVD monitoring a reality. During the real-time Electrocardiography (ECG) acquisition, proper detection of individual ECG beats, and the extraction of essential features from each ECG beat is crucial to automate the diagnosis process of CVD remotely. Therefore, it is necessary to explore various techniques for the detection of CVD and the complexity involved in it. This chapter does the review and covers various methods to process the ECG signal and focuses on the low complexity algorithms to extract the significant clinical features of ECG.

Keywords

ECG Boundary detection Feature extraction Discrete wavelet transform Fragmented QRS Cardiovascular diseases 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Department of Electrical EngineeringIIT HyderabadKandi, SangareddyIndia

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