International Journal of Electrical, Electronics and Data Communication (IJEEDC)
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Statistics report
Dec. 2022
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 116
Paper Published : 1605
No. of Authors : 4403
  Journal Paper


Paper Title :
Cardiac Arrhythmia Detection through ECG Signals

Author :Ravina D. Edake, Anita Patil

Article Citation :Ravina D. Edake ,Anita Patil , (2018 ) " Cardiac Arrhythmia Detection through ECG Signals " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 61-64, Volume-6,Issue-8

Abstract : Electrocardiogram (ECG) signals are widely used for detecting & diagnosing the abnormalities related to heart (CVDs). ECG signal has number of cardiac cycles & each cardiac cycle has PQRST wave. Cardiovascular diseases are widely classified as hypertensive, rheumatic, congenital etc. One of the abnormalities related to heart is cardiac arrhythmia. In this paper, the ECG signals were taken from MITBIH arrhythmia database. To extract the features from the filtered signal, discrete wavelet transform was used. Finally, all the features calculated were given to classifiers such as K Nearest Neighbor & Support Vector Machine to classify the signals into normal & abnormal signal class. Keywords - Electrocardiogram (ECG), Cardiovascular Diseases (CVDs), beats per minute (bpm), Discrete Wavelet Transform (DWT), Daubechies Wavelet 4 (Db4), K Nearest Neighbor (KNN), Support Vector Machine (SVM), Accuracy (Acc), Sensitivity (Se), Specificity (Sp)

Type : Research paper

Published : Volume-6,Issue-8


DOIONLINE NO - IJEEDC-IRAJ-DOIONLINE-13351   View Here

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