Classification of heart diseases from ECG signals using wavelet transform and kNN classifier

Author

Saini, Ridhi ; Bindal, Namita ; Bansal, Puneet

Author_Institution

Electron. & Commun. Eng. Dept., Kurukshetra Univ., Kurukshetra, India

fYear

2015

fDate

15-16 May 2015

Firstpage

1208

Lastpage

1215

Abstract

Heart is the most vital organ which circulates blood along with nutrients and oxygen throughout the body. There are number of reasons which may affect its normal working. In this paper ten heart diseases, as well as normal, have been classified by extracting features from original ECG (electrocardiogram) signals and sixth level wavelet transformed ECG signals. The results have been compared and improved accuracy has been obtained using wavelet transformed signals.

Keywords

electrocardiography; feature extraction; learning (artificial intelligence); medical signal processing; signal classification; wavelet transforms; ECG signals; electrocardiography; feature extraction; heart disease classification; k-nearest neighbor; kNN classifier; wavelet transform; Electrocardiography; Feature extraction; Fibrillation; Heart rate variability; Pregnancy; Rhythm; Wavelet transforms; Classification algorithm; Discrete wavelet transforms; Electrocardiography; Principal component analysis; Statistical analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Computing, Communication & Automation (ICCCA), 2015 International Conference on

Conference_Location

Noida

Print_ISBN

978-1-4799-8889-1

Type

conf

DOI

10.1109/CCAA.2015.7148561

Filename

7148561