Palaniappan Ramaswamy
Department of Computing and Electronic Systems, University of Essex, Colchester, CO4 3SQ, United Kingdom.
Int J Neural Syst. 2008 Feb;18(1):59-66. doi: 10.1142/S0129065708001373.
Brain waves are proposed as a biometric for verification of the identities of individuals in a small group. The approach is based on a novel two-stage biometric authentication method that minimizes both false accept error (FAE) and false reject error (FRE). These brain waves (or electroencephalogram (EEG) signals) are recorded while the user performs either one or several thought activities. As different individuals have different thought processes, this idea would be appropriate for individual authentication. In this study, autoregressive coefficients, channel spectral powers, inter-hemispheric channel spectral power differences, inter-hemispheric channel linear complexity and non-linear complexity (approximate entropy) values were used as EEG features by the two-stage authentication method with a modified four fold cross validation procedure. The results indicated that perfect accuracy was obtained, i.e. the FRE and FAE were both zero when the proposed method was tested on five subjects using certain thought activities. This initial study has shown that the combination of the two-stage authentication method with EEG features from thought activities has good potential as a biometric as it is highly resistant to fraud. However, this is only a pilot type of study and further extensive research with more subjects would be necessary to establish the suitability of the proposed method for biometric applications.
脑电波被提议作为一种生物特征识别技术，用于验证小群体中个体的身份。该方法基于一种新颖的两阶段生物特征认证方法，该方法可将误识率（FAE）和拒识率（FRE）降至最低。这些脑电波（或脑电图（EEG）信号）是在用户执行一项或多项思维活动时记录的。由于不同个体的思维过程不同，因此该方法适用于个体认证。在本研究中，自回归系数、通道频谱功率、半球间通道频谱功率差异、半球间通道线性复杂度和非线性复杂度（近似熵）值被用作脑电图特征，采用改进的四重交叉验证程序的两阶段认证方法。结果表明，当使用特定思维活动对五名受试者进行测试时，该方法获得了完美的准确率，即FRE和FAE均为零。这项初步研究表明，两阶段认证方法与思维活动的脑电图特征相结合，作为一种生物特征识别技术具有很大的潜力，因为它具有很强的抗欺诈能力。然而，这只是一项试点研究，需要对更多受试者进行进一步广泛的研究，以确定该方法在生物特征识别应用中的适用性。
