An Electrocardiogram Classification Method Based On Cascade Support Vector Machine

摘要：

In this paper, a method based on cascade Support Vector Machine (SVM) to classify electrocardiogram (ECG) has been proposed. First, we extract features by threshold based method and Independent Component Analysis (ICA) method. And then we discuss the construction of the model. When using SVM, we focus on how to choose the parameters, how to structure these sub-classifiers, and how to filter data which is diagnosed by former classifier. At last, experiments which used the practical multi-lead data collected from patients of remote medical center are presented. For 2-classification experiment, the accuracy of testing data is 91.59％.

关键词： Support Vector Machine Multi-lead ECG classification Cascade Classifier

作者: Jiangchao Zhu Mi Shen Kanjie Zhu

作者单位: Software Engineering Institute East China Normal University Shanghai, China

会议类型: 国际会议

会议名称: 2011 4th International Conference on Biomedical Engineering and Informatics(第四届生物医学工程与信息学国际会议 BMEI 2011)

会议地点: 上海

会议语种:英文

页码: 1652-1656

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）