TY - GEN
T1 - Classification of cardiac arrhythmias using biorthogonal wavelet preprocessing and SVM
AU - Abibullaev, Berdakh
AU - Kang, Won Seok
AU - Lee, Seung Hyun
AU - An, Jinung
PY - 2010/7/26
Y1 - 2010/7/26
N2 - In the current study we present a technique for the detection and classification of cardiac arrhythmias using biorthogonal wavelet functions and support vector machines (SVM). First, the wavelet transforms is applied to decompose the ECG signal into wavelet scales. Further, a soft thresholding technique is used to denoise and detect important cardiac events in the signal. Subsequently, we applied SVM classifier to discriminate the detected events into normal or pathological ones in the signal. Numeric computations demonstrate that the efficient wavelet pre-processing provides an accurate estimation of important physiological features of ECG and moreover it improves the SVM classification performance.
AB - In the current study we present a technique for the detection and classification of cardiac arrhythmias using biorthogonal wavelet functions and support vector machines (SVM). First, the wavelet transforms is applied to decompose the ECG signal into wavelet scales. Further, a soft thresholding technique is used to denoise and detect important cardiac events in the signal. Subsequently, we applied SVM classifier to discriminate the detected events into normal or pathological ones in the signal. Numeric computations demonstrate that the efficient wavelet pre-processing provides an accurate estimation of important physiological features of ECG and moreover it improves the SVM classification performance.
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M3 - Conference contribution
AN - SCOPUS:77954809357
SN - 9788988678206
T3 - INC2010 - The International Conference on Networked Computing, Proceeding
SP - 332
EP - 336
BT - INC2010 - The International Conference on Networked Computing, Proceeding
T2 - 6th International Conference on Networked Computing, INC2010
Y2 - 11 May 2010 through 13 May 2010
ER -