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International Journal of Technology Enhancements and Emerging Engineering Research (ISSN 2347-4289)
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IJTEEE >> Volume 2 - Issue 5, May 2014 Edition



International Journal of Technology Enhancements and Emerging Engineering Research  
International Journal of Technology Enhancements and Emerging Engineering Research

Website: http://www.ijteee.org

ISSN 2347-4289



Compression And Classification Of Ecg Signal Based On Morphological And Dynamic Features

[Full Text]

 

AUTHOR(S)

Lourdu nancy.P, T.Anna Sudha M.E.

 

KEYWORDS

Keywords: ECG, Set Partitioning in Hierarchical Tress (SPIHT), GK cluster, Support Vector Machine (SVM)

 

ABSTRACT

Abstract: ECG generated waveforms are used to find patterns of irregularities in cardiac cycle in patients. In order to provide continuous monitoring of cardiac functions for real time diagnosis we propose a methodology that combines compression and analysis of heart beat. In this paper an efficient ECG signal compression method based on wavelet transform is presented. The proposed method combines the adapted SPIHT compression. The tests of this compression can be performed on many ECG records. We propose a new approach for heartbeat classification based on combination of morphological and dynamic features using GK clustering. The GK clustering classifies the signal better than SVM because GK clustering technique compares the training and testing data’s not only based on the simple threshold also based on the more number of features for comparison.

 

REFERENCES

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