Biometric identification using fingertip electrocardiogram signals
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Dosyalar
Tarih
2018-07
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer London Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this research work, we present a newly fingertip electrocardiogram (ECG) data acquisition device capable of recording the lead-1 ECG signal through the right- and left-hand thumb fingers. The proposed device is high-sensitive, dry-contact, portable, user-friendly, inexpensive, and does not require using conventional components which are cumbersome and irritating such as wet adhesive Ag/AgCl electrodes. One of the other advantages of this device is to make it possible to record and use the lead-1 ECG signal easily in any condition and anywhere incorporating with any platform to use for advanced applications such as biometric recognition and clinical diagnostics. Furthermore, we proposed a biometric identification method based on combining autocorrelation and discrete cosine transform-based features, cepstral features, and QRS beat information. The proposed method was evaluated on three fingertip ECG signal databases recorded by utilizing the proposed device. The experimental results demonstrate that the proposed biometric identification method achieves person recognition rate values of 100% (30 out of 30), 100% (45 out of 45), and 98.33% (59 out of 60) for 30, 45, and 60 subjects, respectively.
Açıklama
Anahtar Kelimeler
Fingertip ECG data acquisition device, Fingertip ECG signal, Feature extraction, Classification, Biometric identification, ECG, Segmentation, Recognition, Information, Biometrics, Electrocardiography, ECG biometric, Anthropometry, Classification (of information), Data acquisition, Discrete cosine transforms, Biometric identification methods, Biometric recognition, Conventional components, Data-acquisition devices, Ecg data acquisitions, ECG signals, Electrocardiogram signal, Biomedical signal processing
Kaynak
Signal, Image and Video Processing
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
12
Sayı
5
Künye
Güven, G., Gürkan, H. & Güz, Ü. (2018). Biometric identification using fingertip electrocardiogram signals. Signal, Image and Video Processing, 12(5), 933-940. doi:10.1007/s11760-018-1238-4
