Title :
Classifying electrocardiogram peaks using newwavelet domain features
Author :
Vansteenkiste, E. ; Houben, R. ; Pizurica, A. ; Philips, W.
Author_Institution :
Ghent Univ., Ghent
Abstract :
We study distinctive properties of normal and malfunction electrocardiogram (ECG) peaks in the wavelet domain and based on this study we propose novel classification features for ECG signals. We analyze different combinations of the proposed wavelet domain and time domain features using multidimensional clustering and dimensionality reduction techniques. The results indicate encouraging accuracy rates.
Keywords :
data reduction; electrocardiography; feature extraction; medical signal processing; pattern classification; pattern clustering; statistical analysis; waveform analysis; ECG peak classification; ECG signal classification features; dimensionality reduction techniques; electrocardiogram; malfunction ECG peak; multidimensional clustering techniques; normal ECG peak; time domain features; wavelet domain features; Atrial fibrillation; Electrocardiography; Heart beat; Instruments; Multidimensional systems; Shape; Time domain analysis; Wavelet analysis; Wavelet coefficients; Wavelet domain;
Conference_Titel :
Computers in Cardiology, 2008
Conference_Location :
Bologna
Print_ISBN :
978-1-4244-3706-1
DOI :
10.1109/CIC.2008.4749176
