摘要： 基于心电信号的身份识别是研究生物特征身份识别中的热点。在研究基于心电波形基准点方法的基础上,根据获得的特征在身份识别中的贡献率,提出一种特征的筛选策略。利用心电波形基准点的实际检测准确率,修正特征的原有贡献率,得到可应用的实际贡献率,从而获得优化后的可用于身份识别的关键特征集。采用PTB数据集和自采数据集进行实验,结果表明,经筛选策略修正后,PTB数据集用于识别的特征从9个增至12个,自采数据集的特征从17个增至18个,身份识别准确率分别达到98.7%和90.21%。

关键词: 基准点检测, 特征贡献率, 心电信号, 身份识别, 逐步判别, 生物特征

Abstract: Identification based on Electrocardiogram(ECG)signal is an emerging study hotspot in biometric identification.This paper proposes a feature selecting strategy.The fiducial point detection accuracy is used to modify the original contribution rate of the feature,so as to obtain the real applicable contribution rate and the key feature set for identification.This paper adopts the Physikalisch-technische Bundesanstalt(PTB)data sets and self-collecting ECG data sets.Experimental result shows that the proposed strategy increases the features of PTB data sets from 9 to 12 and that of self-collecting data sets from 17 to 18.Identification accuracy reaches 98.7% and 90.21% respectively.

Key words: fiducial point detection, feature contribution rate, Electrocardiogram(ECG) signal, Identification, stepwise discriminant, biometric feature

中图分类号: 

• TP18