Bio-Signal Authentication Algorithm Using Electrocardiogram 


Vol. 42,  No. 12, pp. 2350-2356, Dec.  2017
10.7840/kics.2017.42.12.2350


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  Abstract

Traditionally, biometric technologies have become widely available in many ways, including immigration, access control, administration, social welfare, medical care, and information and communications finance. In recent years, they have become emerge as the non-face-to-face technology in Fin-tech area such as mobile payments service, ATMs, and Internet banking. However, biometric technologies using existing physical features such as fingerprint, facial, iris and vein can be concerned about the forgery and alternations of biometric technologies using fake physical characteristics such as fake fingerprints. So, it is stepping up the trend toward next-generation biometric technologies using behavioral biometrics of a living person such as bio-signals and walking. Accordingly, in this paper, we are developing bio-signal authentication algorithm using ECG which most personally identifiable among bio-signals such as EEG, ECG, PPG and EMG. When using ECG signal, personal identification and authentication accuracy are around 90% in rest state. Also, the change in posture and electrode position are almost unchanged with 0.98, but it shows the lowest ECG waveform matching with 0.72 when the heart rate changed due to exercise.

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  Cite this article

[IEEE Style]

S. Lee and J. Kim, "Bio-Signal Authentication Algorithm Using Electrocardiogram," The Journal of Korean Institute of Communications and Information Sciences, vol. 42, no. 12, pp. 2350-2356, 2017. DOI: 10.7840/kics.2017.42.12.2350.

[ACM Style]

Saewoom Lee and Jason Kim. 2017. Bio-Signal Authentication Algorithm Using Electrocardiogram. The Journal of Korean Institute of Communications and Information Sciences, 42, 12, (2017), 2350-2356. DOI: 10.7840/kics.2017.42.12.2350.

[KICS Style]

Saewoom Lee and Jason Kim, "Bio-Signal Authentication Algorithm Using Electrocardiogram," The Journal of Korean Institute of Communications and Information Sciences, vol. 42, no. 12, pp. 2350-2356, 12. 2017. (https://doi.org/10.7840/kics.2017.42.12.2350)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880