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基于小波变换的12-导联心电图特征提取方法
Feature Extraction Method for 12-Lead ECG Based on Wavelet Transform
【摘要】 提出了一种基于小波多分辨分析的算法对心电信号进行特征提取和识别.通过小波变换对常规12-导联心电图进行分段和特征提取,并利用支撑向量机和提取的特征向量对未知心电图进行分类.实验结果表明该方法具有较好的应用前景.
【Abstract】 An algorithm to extract features of electro-cardio-gram (ECG) signal based on wavelet multiresolution analysis is developed. The wavelet transform is used for the segmentation and the feature extraction of ordinary 12-lead ECG. The support vector machine is used to classify the unknown ECG signal. The result shows that feature extraction technology has an optimistic prospect.
【关键词】 分段;
特征抽取;
小波变换;
支撑向量机;
心电图分类;
【Key words】 segmentation; feature extraction; wavelet transform; support vector machine; ECG classification;
【Key words】 segmentation; feature extraction; wavelet transform; support vector machine; ECG classification;
【基金】 国家自然科学基金(C03020708)上海市高等学校青年科学基金(03HQ20)
- 【文献出处】 华东师范大学学报(自然科学版) ,Journal of Eastchina Normal University(Natural Science) , 编辑部邮箱 ,2005年02期
- 【分类号】R318.04
- 【被引频次】22
- 【下载频次】315