| 基于SVM的ECG传感器信号身份识别方法 |
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| 引用本文： | 陈曦,陈冠雄,沈海斌. 基于SVM的ECG传感器信号身份识别方法[J]. 传感器与微系统, 2014, 33(10): 40-42 |
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| 作者姓名： | 陈曦 陈冠雄 沈海斌 |
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| 作者单位： | 1. 浙江大学超大规模集成电路设计研究所,浙江杭州,310027
2. 杭州易和网络有限公司,浙江杭州,310012 |
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| 摘 要： | 通过心电图（ECG）传感器采集的信号在身份识别中得到了越来越广泛的应用.但小波滤噪结果往往通过主观判断,没有量化指标,滤波效果不理想;同时,对于ECG特征的提取没有考虑心率变化的影响,鲁棒性不佳.针对这2个问题,提出了一种通过信噪比和相关系数衡量预处理结果的办法,并且在特征的提取上只采用QRS波形,避开了易受心率影响的间期特征.最后使用了多种分类识别方法进行测试,得到了小样本下支持向量机（SVM）最适用于ECG识别的结论.
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| 关 键 词： | 心电图 小波变换 支持向量机 相关系数 特征提取 分类识别 |
ECG sensor signal identification method based on SVM |
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| CHEN Xi,CHEN Guan-xiong,SHEN Hai-bin. ECG sensor signal identification method based on SVM[J]. Transducer and Microsystem Technology, 2014, 33(10): 40-42 |
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| Authors: | CHEN Xi CHEN Guan-xiong SHEN Hai-bin |
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| Affiliation: | CHEN Xi, CHEN Guan-xiong , SHEN Hai-bin ( 1. Institute of VLSI Design, Zhejiang University, I-Iangzhou 310027, China; 2. Yihe Company Limited, Hangzhou 310012 ,China) |
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| Abstract: | ECG signal collected by ECG sensor is widely used in field of identification. Firstly, wavelet de-noising results are often judged subjectively, no quantitative indicators, and filtering effect is not ideal. Secondly, influence of change of heart rate isn＇ t taken into consideration, robustness is poor. In order to solve these two problems, put forward a kind of methods to measure results of pretreatment by SNR and correlation coefficient, and only adopt QRS waveform in feature extraction, avoiding interval feature easily influenced by heart rate. Finally, use a variety of classification and recognition methods for testing~ for small sample, SVM is most suitable for ECG identification. |
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| Keywords: | ECG wavelet transform SVM correlation coefficient feature extraction classification identification |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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