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EEG Fingerprints under Naturalistic Viewing Using a Portable Device

机译:使用便携式设备进行自然性观看的EEG指纹

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摘要

The electroencephalogram (EEG) has been proven to be a promising technique for personal identification and verification. Recently, the aperiodic component of the power spectrum was shown to outperform other commonly used EEG features. Beyond that, EEG characteristics may capture relevant features related to emotional states. In this work, we aim to understand if the aperiodic component of the power spectrum, as shown for resting-state experimental paradigms, is able to capture EEG-based subject-specific features in a naturalistic stimuli scenario. In order to answer this question, we performed an analysis using two freely available datasets containing EEG recordings from participants during viewing of film clips that aim to trigger different emotional states. Our study confirms that the aperiodic components of the power spectrum, as evaluated in terms of offset and exponent parameters, are able to detect subject-specific features extracted from the scalp EEG. In particular, our results show that the performance of the system was significantly higher for the film clip scenario if compared with resting-state, thus suggesting that under naturalistic stimuli it is even easier to identify a subject. As a consequence, we suggest a paradigm shift, from task-based or resting-state to naturalistic stimuli, when assessing the performance of EEG-based biometric systems.
机译:已被证明是脑电图(EEG)是有希望的个人识别和验证的技术。最近,显示了功率谱的非周期性组分以优于其他常用的EEG特征。除此之外,EEG特征可能捕捉与情绪状态相关的相关特征。在这项工作中,我们旨在了解功率谱的非周期性组件,如图所示用于休息状态实验范式,可以在自然主义刺激场景中捕获基于EEG的主题特征。为了回答这个问题,我们使用两个可自由的数据集进行了分析,其中包括来自参与者的eEG录像期间的档案剪辑,该数据涉及触发不同的情绪状态。我们的研究证实,根据偏移和指数参数评估的功率谱的非周期性组件能够检测从头皮EEG提取的主题特征。特别是,我们的结果表明,如果与休息状态相比,薄膜剪辑场景的系统的性能显着更高,因此表明在自然刺激下,甚至更容易识别受试者。因此,在评估基于EEG的生物识别系统的性能时,我们建议从基于任务或休息状态到自然刺激的范式转变。

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