Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | INC2010 - The International Conference on Networked Computing, Proceeding |
| Pages | 332-336 |
| Number of pages | 5 |
| Publication status | Published - Jul 26 2010 |
| Event | 6th International Conference on Networked Computing, INC2010 - Gyeongju, Korea, Republic of Duration: May 11 2010 → May 13 2010 |
Publication series
| Name | INC2010 - The International Conference on Networked Computing, Proceeding |
|---|
Other
| Other | 6th International Conference on Networked Computing, INC2010 |
|---|---|
| Country | Korea, Republic of |
| City | Gyeongju |
| Period | 5/11/10 → 5/13/10 |
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Computer Networks and Communications
- Software
Fingerprint Dive into the research topics of 'Classification of cardiac arrhythmias using biorthogonal wavelet preprocessing and SVM'. Together they form a unique fingerprint.
Cite this
Abibullaev, B., Kang, W. S., Lee, S. H., & An, J. (2010). Classification of cardiac arrhythmias using biorthogonal wavelet preprocessing and SVM. In INC2010 - The International Conference on Networked Computing, Proceeding (pp. 332-336). [5484804] (INC2010 - The International Conference on Networked Computing, Proceeding).