Title :
Automated Prediction of Spontaneous Termination of Paroxysmal Atrial Fibrillation Using Support Vector Machine
Author :
Huang, Zhongchao ; Chen, Zhencheng ; Zhao, Yuqian
Author_Institution :
Sch. of Info-Phys. & Geomatics Eng., Central South Univ., Changsha
Abstract :
Based on our previous work, we develop a classifier using support vector machine to differentiate paroxysmal atrial fibrillation (AF) from sustained AF and propose an automatic scheme to predict the spontaneous termination of paroxysmal AF. Experimental studies over the challenge database of Physionet/CinC 2004 show that our method is able to achieve high classification accuracy and is fairly reliable. This in turn justifies our previous work.
Keywords :
diseases; electrocardiography; medical signal processing; signal classification; support vector machines; ECG signals; automated prediction analysis; cardiac arrhythmia; classification method; paroxysmal atrial fibrillation; support vector machine; Artificial neural networks; Atrial fibrillation; Biomedical engineering; Data engineering; Databases; Electrocardiography; Electronic mail; Support vector machine classification; Support vector machines; Testing;
Conference_Titel :
Bioinformatics and Biomedical Engineering, 2007. ICBBE 2007. The 1st International Conference on
Conference_Location :
Wuhan
Print_ISBN :
1-4244-1120-3
DOI :
10.1109/ICBBE.2007.163
