基于图像刺激的脑电分析生物特征认证方法的提出与评价

Masato Yamashita, M. Nakazawa, Yukinobu Nishikawa
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引用次数: 1

摘要

近年来,利用人脑活动进行人机交流和机器人操作的脑机接口(BMI)技术得到了广泛的研究。这是一种可以实时测量脑电图(EEG)的无创脑电图仪的结果。但目前的现状是,对BMI的鉴定方法研究较少。在我们的研究中,我们提出了一种基于图像刺激的脑电图生物识别认证方法。在这项研究中,我们提出了一种基于图像刺激的脑电图生物识别认证方法。在本文中,我们构建并评估了一个利用脑电在图像刺激下进行生物识别认证的系统。我们使用互相关系数进行特征提取,并使用支持向量机进行分类/认证。此外,我们还考虑了预处理方法(数字滤波、伪影对抗、历元),验证了更合适的预处理方法。我们验证了所提出的方法。采用伪干扰、数字滤波(IIR滤波)和历元法后,系统的干扰系数为2.0%。根据FAR和FRR的结果,提出了采用伪干扰来提高系统精度的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Proposal and It’s Evalution of Biometric Authentication Method by EEG Analysis Using Image Stimulation
In recent years, techniques of Brain Machine Interface (BMI) which conducts human communication and robot manipulation using human brain activity are widely researched. This is the result of a noninvasive electroencephalograph device that can measure Electroencephalogram (EEG) in real time. However, there is a present condition that the authentication method when BMI is not much researched. In our research, we propose a biometric authentication method of electroencephalogram using image stimulation. In this research, we propose a biometric authentication method of electroencephalogram using image stimulation. In this paper, we construct and then evaluate a system that performs biometric authentication using EEG at image stimulus. We perform feature extraction using cross-correlation coefficient, and SVM for classification / authentication. Moreover We considered the method for preprocessing (digital filter, artifact countermeasure, epoch), we verify more appropriate preprocessing method. We verified the proposed method. In our proposed system, EER: 2.0% was obtained when artifact countermeasure, digital filter (IIR filter), and epoch method were used. From the result of FAR and FRR, our system was suggested that accuracy is improved by taking artifact countermeasure.
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