Title :
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
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;
Conference_Titel :
Computing, Communication & Automation (ICCCA), 2015 International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-8889-1
DOI :
10.1109/CCAA.2015.7148561
