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http://dx.doi.org/10.9718/JBER.2014.35.3.42

Identification of Individuals using Single-Lead Electrocardiogram Signal  

Lim, Seohyun (Department of Biomedical Engineering, Hanyang University)
Min, Kyeongran (Department of Biomedical Engineering, Hanyang University)
Lee, Jongshill (Department of Biomedical Engineering, Hanyang University)
Jang, Dongpyo (Department of Biomedical Engineering, Hanyang University)
Kim, Inyoung (Department of Biomedical Engineering, Hanyang University)
Publication Information
Journal of Biomedical Engineering Research / v.35, no.3, 2014 , pp. 42-49 More about this Journal
Abstract
We propose an individual identification method using a single-lead electrocardiogram signal. In this paper, lead I ECG is measured from subjects in various physical and psychological states. We performed a noise reduction for lead I signal as a preprocessing stage and this signal is used to acquire the representative beat waveform for individuals by utilizing the ensemble average. From the P-QRS-T waves, features are extracted to identify individuals, 19 using the duration and amplitude information, and 16 from the QRS complex acquired by applying Pan-Tompkins algorithm to the ensemble averaged waveform. To analyze the effect of each feature and to improve efficiency while maintaining the performance, Relief-F algorithm is used to select features from the 35 features extracted. Some or all of these 35 features were used in the support vector machine (SVM) learning and tests. The classification accuracy using the entire feature set was 98.34%. Experimental results show that it is possible to identify a person by features extracted from limb lead I signal only.
Keywords
individual identification; single-lead; electrocardiogram; ensemble average;
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