Wavelet distance measure for person identification using electrocardiograms
Wavelet distance measure for person identification using electrocardiograms
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DOI：
10.1109/tim.2007.909996
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发表时间：
2008-02-01
影响因子：
5.6
通讯作者：
Badee, Vesal
中科院分区：
文献类型：
--
作者：
Chan, Adrian D. C.;Hamdy, Mohyeldin M.;Badee, Vesal
在这篇文章中，作者提出了一种新的基于心电波形的生物识别方法。在不同日期的三次数据记录过程中，受试者使用一个简单的用户界面收集了50名受试者的心电数据，受试者使用拇指和食指将两个电极放在拇指垫上。第一次会议的数据被用来建立登记数据库，其余两次会议的数据被用作测试案例。分类采用三种不同的量化度量：残差百分比、相关系数和一种新的基于小波变换的距离度量。小波距离度量的分类正确率为89%，比其他方法提高了近10%。这种心电身份识别模式将是对传统生物识别技术的有益补充，如指纹和手掌识别系统。
In this paper, the authors present an evaluation of a new biometric based on electrocardiogram (ECG) waveforms. ECG data were collected from 50 subjects during three data-recording sessions on different days using a simple user interface, where subjects held two electrodes on the pads of their thumbs using their thumb and index fingers. Data from session 1 were used to establish an enrolled database, and data from the remaining two sessions were used as test cases. Classification was performed using three different quantitative measures: percent residual difference, correlation coefficient, and a novel distance measure based on wavelet transform. The wavelet distance measure has a classification accuracy of 89%, outperforming the other methods by nearly 10%. This ECG person-identification modality would be a useful supplement for conventional biometrics, such as fingerprint and palm recognition systems.