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智能汽车脑电图认证访问控制设计

Design of electroencephalogram authentication access control to smart car.

作者信息

Chen Yuhua, Yin Jinghai

机构信息

The Center of Collaboration and Innovation, Jiangxi University of Technology, Yao Lake University Park, Nanchang, 330098, People's Republic of China.

出版信息

Healthc Technol Lett. 2020 Sep 3;7(4):109-113. doi: 10.1049/htl.2019.0092. eCollection 2020 Aug.

Abstract

In recent years, with the development of intelligent vehicles, the demand for security will be bigger and bigger. One of the most important solutions is the use of new biometric technology. At present, there are still some areas to be improved on biometric technology. For example, diseases will destroy some biological characteristics, some detection methods are too slow, many detection methods do not need living detection, and so on. Electroencephalogram (EEG) is a new biometric tool for living identification. In this Letter, a kind of identity authentication system based on the EEG signal is presented. The overall goal of this research is to design a new authentication method and develop the corresponding application. Therefore, the authors carried out a series of EEG experiments, and analysed and discussed the experimental results. Based on these results, they build and present an access control system based on the uniqueness of their EEG signals to be capable of authenticating access control to the car. The accuracy of the authentication system is >87.3%.

摘要

近年来,随着智能汽车的发展,对安全性的需求越来越大。最重要的解决方案之一是使用新的生物识别技术。目前,生物识别技术仍有一些有待改进的地方。例如,疾病会破坏一些生物特征,一些检测方法过于缓慢,许多检测方法不需要活体检测等等。脑电图(EEG)是一种用于活体识别的新型生物识别工具。在这篇信函中,提出了一种基于EEG信号的身份认证系统。本研究的总体目标是设计一种新的认证方法并开发相应的应用。因此,作者进行了一系列EEG实验,并对实验结果进行了分析和讨论。基于这些结果,他们构建并提出了一种基于EEG信号唯一性的访问控制系统,能够对汽车的访问控制进行认证。该认证系统的准确率>87.3%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8d9/7494368/e317ec00e78c/HTL.2019.0092.01.jpg

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