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Analysis of Cognitive Load -- Importance of EEG Channel Selection for Low Resolution Commercial EEG Devices

机译:认知负荷分析 - 低分辨率商业EEG器件EEG频道选择的重要性

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Measurement of cognitive load using brain signalsis an important area of research in human behavior and psychology. Recently, there have been attempts to use low cost, commercially available Electroencephalogram (EEG) devices for the analysis of the cognitive load. Due to the reduced number of leads, these low resolution devices pose major challenges in signal processing as well as in feature extraction. In this paper, we investigate the significant leads or channels that are useful for the analysis of the cognitive load. We use a standard matching test and n-back memory test imparting low and high cognitive loads respectively. The investigation is based on the analysis of variance (ANOVA) of Alpha and Theta frequency band signals for various combinations of leads. Comparisons have been done between the previously reported leads and those obtained using a few feature selection algorithms. Results indicate that for a given stimulus, though the significant leads are very much dependent on the subjects, the leads corresponding to the left frontal lobe and right parieto-occipital lobe are in general most significant across majority of subjects for analysis of the cognitive load.
机译:测量使用脑刺激的认知载荷是人类行为和心理学研究的重要研究领域。最近,已经尝试使用低成本,商业上可用的脑电图(EEG)装置来分析认知载荷。由于引线数量减少,这些低分辨率装置在信号处理以及特征提取中构成了主要挑战。在本文中,我们研究了可用于分析认知载荷的重要引线或通道。我们使用标准匹配测试和施加低和高认知负载的N背记忆测试。该研究基于α和θ频带信号的各方差(ANOVA)的分析,用于引线的各种组合。在先前报告的领导和使用少数特征选择算法获得的那些之间已经完成了比较。结果表明,对于给定的刺激,尽管显着的引线非常依赖于受试者,但对应于左前叶和右侧枕叶的引线通常在大多数受试者中占据了认知载荷的大多数受试者中最重要的。

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