期刊文献+

基于小波分解和数据融合方法的ECG身份识别 被引量:14

Human Identification Based on ECG with Wavelet Decomposition and Data Fusion Method
原文传递
导出
摘要 目的研究一种新的基于ECG的身份识别方法。方法选取35位健康人ECG波形的波形特征、小波特征和融合特征作为特征向量,通过相关系数阈值法进行ECG身份识别。结果对35位被试者的另外40段数据进行身份识别验证,基于波形特征、小波特征、融合特征的身份识别正确率分别为82.5%、87.5%、95%。采用小波特征身份识别的正确率优于波形特征的正确率,而采用融合特征识别的正确率优于其他两种特征的正确率。结论实验表明,基于ECG的身份识别技术是可行的,可以和指纹等多种生物特征联合使用开发多导生物识别系统,并且本文所提方法算法简单,实时性好,准确度高。 Objective A new method is researched based on ECG for human identification.Methods Three features of wave feature,wavelet feature,fusion feature were selected as the feature vectors for 35 normal subject ECGs,and correlation coefficient discriminate analysis was used for human identification. Results The other 40 sessions from 35 subjects were used for verifying the accuracy of each feature.They were 82.5%、87.5% and 95% respectively for wave feature,wavelet feature and fusion feature. ECG wavelet feature outperformed ECG wave feature. While ECG fusion feature performed better than either feature. Conclusion The verification experiment demonstrates that the technology of human identification based on ECG is feasible. ECG can be combined with other biometric features such as fingerprint for developing the multi-biometric identification system. The method proposed in this paper is simple,real-time and exact for human identification.
出处 《航天医学与医学工程》 CAS CSCD 北大核心 2009年第4期296-301,共6页 Space Medicine & Medical Engineering
基金 中国航天医学工程预先研究项目(SJ200903)
关键词 ECG 身份识别 波形特征 小波特征 融合特征 相关系数 ECG human identification wave feature wavelet feature fusion feature correlation coefficient
  • 相关文献

参考文献17

  • 1Agrafioti F, Hatzinakos D. ECG based recognition using second order statistics [ C ]. In : Communication Networks and Services Research Conference, Halifax, Nova Scotia Canada, 2008 : 82-87.
  • 2SUN Dongmei, QIU Zhengding. Biometric trait identilfication technology review [ J ]. Electronic Transaction, 2001, 29 (12) : 1744-1748.
  • 3ZHANG Mingui. Biometric trait identification and research progress[ J ]. Biophysics Transaction, 2002, 18 ( 2 ) : 156- 162.
  • 4Putte T,Keuning J. Biometrical fingerprint recognition don't get your fingers burned [ C ]. Fourth Working Conference on Smart Card Research and Advanced Applications, Bristol, UK, 2000 : 289 -303.
  • 5Chan ADC, Hamdy MM,Badre A, et al. Person identification using electrocardiograms [ C ]. In : Canadian Conference on Electrical and Computer Engineering. Ottawa, Canada,2006: 1-4.
  • 6Biel L,Pettersson O,Philipson L, et al. ECG analysis: a new approach in human identification[ J]. IEEE Trans. on Instrumentation and Measurement, 2001,50 (3) : 808-812.
  • 7Kim KS, Yoon TH,Lee ,JW et al. A robust human identification by normalized time-domain features of electrocardiogram [ C ]. In : Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. Shanghai, China,2005:1114-1117.
  • 8Shen TW,TompkinsWJ, Hu YH. One-lead ECG for identity verification[ C]. In: 2nd Joint Conference of the IEEE Engineering in Medicine and Biology Society and Biomedical Engineering Society, Houston,2002:62-63.
  • 9Wang Y, Plataniotis KN, Hatzinakos D. Integrating analytic and appearance attributes for human identification from ECG signal[ C]. In: Proc. of Biometrics Symposiums (BSYM). Baltimore, Maryland, USA, 2006 : 1 -5.
  • 10HE Wei, CHEN Liangchi, XU Xiaohong. The research of the frequency of ECG segment and available bandwidth [ J ]. Biomedicine Transaction, 1996,13 (4) : 336-340.

同被引文献138

引证文献14

二级引证文献37

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部