International Journal of Electrical, Electronics and Data Communication (IJEEDC)
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May. 2022
Submitted Papers : 80
Accepted Papers : 10
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Acc. Perc : 12%
Issue Published : 111
Paper Published : 1546
No. of Authors : 4203
  Journal Paper


Paper Title :
Performance Appraisal of DWT and PCA Based Cardiac ECG Arrhythmias Diagnosis With K-NN Classifier

Author :Inbalatha.M, Kalaivani.S

Article Citation :Inbalatha.M ,Kalaivani.S , (2017 ) " Performance Appraisal of DWT and PCA Based Cardiac ECG Arrhythmias Diagnosis With K-NN Classifier " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 32-35, Volume-5,Issue-2

Abstract : Empathy of heart infirmity refined as disorder is real complex in medicinal ground. A standard diagnosis tool Electrocardiogram (ECG) signal is picked to distinguish regular and arrhythmias heart weary. This research exertion develops a unique sketch for feature extraction technique based on Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). The objective of this effort is to succeed a resourceful arrhythmia discovery classification that can clue to high vibrating early heart diagnosis. Euclidean minimum distance norm is nearly new to find least possible distances and k- nearest neighbor classifier is used to classify the heart beats. Faithfully thirteen signals from the MIT-BIH arrhythmias ECG Database has been used for the training and testing the k-NN classifier. In the simulation result, DWT features works worthy for the classifier with the utmost accuracy of 94.4% whereas the accuracy is solitary 70.8% by PCA Keywords- Cardiac arrhythmia, ECG, DWT, k-NN classifier, PCA.

Type : Research paper

Published : Volume-5,Issue-2


DOIONLINE NO - IJEEDC-IRAJ-DOIONLINE-6983   View Here

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