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Yayın Biometric identification using fingertip electrocardiogram signals(Springer London Ltd, 2018-07) Güven, Gökhan; Gürkan, Hakan; Güz, ÜmitIn 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.Yayın An efficient ECG data compression technique based on predefined signature and envelope vector banks(IEEE, 2005) Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık BinboğaIn this paper, a new method to compress ElectroCardioGram (ECG) Signal by means of "Predefined Signature and Envelope Vector Banks-PSEVB" is presented. In this work, on a frame basis, any ECG signal is modeled by multiplying three parameters as called the Predefined Signature Vector, Predefined Envelope Vector, and Frame-Scaling Coefficient. It has been demonstrated that the predefined signature vectors and predefined envelope vectors constitute a "PSEVB" to describe any measured ECG signal. In this case, ECG signal for each frame is described in terms of the two indices "R" and "K" of PSEVB and the frame-scaling coefficient. The new compression method achieve good compression ratios with low level reconstruction error while preserving diagnostic information in the reconstructed ECG signal. Furthermore, once PSEVB are stored on each communication node, transmission of ECG signals reduces to the transmission of indexes "R" and "K" of PSEVB and the frame-scaling coefficient which also result in considerable saving in the transmission band.Yayın A novel hybrid electrocardiogram signal compression algorithm with low bit-rate(Springer, 2010) Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık BinboğaIn this paper, a novel hybrid Electrocardiogram (ECG) signal compression algorithm based on the generation process of the Variable-Length Classified Signature and Envelope Vector Sets (VL-CSEVS) is proposed. Assessment results reveal that the proposed algorithm achieves high compression ratios with low level reconstruction error while preserving diagnostic information in the reconstructed ECG signal. The proposed algorithm also slightly outperforms others for the same test dataset.
