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This study aims to evaluate users’ attention levels under different lighting environments by measuring and analyzing brainwaves. Participants are asked to perform paper-based tests in a simulated office environment, while their brainwave signals are recorded. Each session of the experiment includes two tests to find the target words, 10 minutes each in Chinese and English, followed by 5-minute relaxation with closed eyes. The process is carried out in 12 lighting scenarios arranged by the Latin-square design, with the illuminance at 4 levels (250, 500, 750, 1000 lx) and the correlated color temperature at 3 levels (2690K, 3840K, 4990K). The acquired brainwave signals are processed by Hilbert-Huang transform to find the marginal spectra of intrinsic mode functions. The marginal spectra are then used to compute the corresponding powers in the alpha, beta, and gamma bands, which are called the band powers. By collecting the band power data of 24 participants, the power histogram in each band is plotted and normalized to be the probability density function. The receiver operating characteristic (ROC) analysis is then utilized to suggest the candidates of attention index based on the classification accuracy of binary discrimination tasks. The area under the ROC curve (AUC) for comparing the working and relaxing states is more than 0.85, which indicates sufficient classification accuracy. Moreover, the AUC between different lighting scenarios can be more than 0.65. According to the results, we have confirmed that the method has the potential for attention evaluation of office lighting environments.
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