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Sensors 2017, 17(1), 125; doi:10.3390/s17010125

An Approach to Biometric Verification Based on Human Body Communication in Wearable Devices

Shenzhen Institutes of Advanced Technology, Chinese Academy of Science, Shenzhen 518055, China
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Academic Editors: Giancarlo Fortino, Hassan Ghasemzadeh, Wenfeng Li, Yin Zhang and Luca Benini
Received: 13 October 2016 / Revised: 2 January 2017 / Accepted: 4 January 2017 / Published: 10 January 2017
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Abstract

In this paper, an approach to biometric verification based on human body communication (HBC) is presented for wearable devices. For this purpose, the transmission gain S21 of volunteer’s forearm is measured by vector network analyzer (VNA). Specifically, in order to determine the chosen frequency for biometric verification, 1800 groups of data are acquired from 10 volunteers in the frequency range 0.3 MHz to 1500 MHz, and each group includes 1601 sample data. In addition, to achieve the rapid verification, 30 groups of data for each volunteer are acquired at the chosen frequency, and each group contains only 21 sample data. Furthermore, a threshold-adaptive template matching (TATM) algorithm based on weighted Euclidean distance is proposed for rapid verification in this work. The results indicate that the chosen frequency for biometric verification is from 650 MHz to 750 MHz. The false acceptance rate (FAR) and false rejection rate (FRR) based on TATM are approximately 5.79% and 6.74%, respectively. In contrast, the FAR and FRR were 4.17% and 37.5%, 3.37% and 33.33%, and 3.80% and 34.17% using K-nearest neighbor (KNN) classification, support vector machines (SVM), and naive Bayesian method (NBM) classification, respectively. In addition, the running time of TATM is 0.019 s, whereas the running times of KNN, SVM and NBM are 0.310 s, 0.0385 s, and 0.168 s, respectively. Therefore, TATM is suggested to be appropriate for rapid verification use in wearable devices. View Full-Text
Keywords: biometric verification; human body communication; threshold-adaptive template matching; weighted Euclidean distance; transmission gain S21; wearable device biometric verification; human body communication; threshold-adaptive template matching; weighted Euclidean distance; transmission gain S21; wearable device
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Li, J.; Liu, Y.; Nie, Z.; Qin, W.; Pang, Z.; Wang, L. An Approach to Biometric Verification Based on Human Body Communication in Wearable Devices. Sensors 2017, 17, 125.

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