| 摘要(英) |
This study simulates an indoor reading environment by using desk lamps and ceiling lights to create different illuminance uniformity conditions as lighting scenarios. These scenarios include focused light with only the desk lamp on, uniform light with only the ceiling light on, and mixed light with both the desk lamp and ceiling light on. It aims to explore the physiological and psychological effects of lighting on users and the differences in users’ levels of concentration under various scenarios. The study will adopt the lighting human factors assessment techniques previously used by the research team in the laboratory. Participants will be recruited to take static paper tests, and the impact of the designed scenarios on the participants will be analyzed.
In terms of data measurement, a Neurosky EEG device will be used to measure and record the participants′ brainwave signals while they perform intelligence tests, d2-tests, and during rest sessions in different lighting scenarios to facilitate subsequent analysis. The experimental analysis will employ empirical mode decomposition (EMD), Hilbert transform (HT), probability density function (PDF), and receiver operating characteristic curve (ROC curve) for computation. Objective indicators include the performance on intelligence tests and d2-tests, the area under the curve (AUC) of the receiver operating characteristic curve, and the attention score derived from brainwave features. Subjective indicators will be based on self-assessment questionnaires filled out by the participants. Both objective and subjective indicators will be analyzed using statistical software SPSS to conduct variance analysis and determine whether there are significant differences among the different scenarios, thereby investigating the impact of lighting on the participants.
The results indicate that, in terms of objective indicators, there is no significant classification difference in brainwaves between different scenarios during concentration and rest. The performance on intelligence tests and d2-tests also shows no significant differences between scenarios, although there is a practice effect observed in the d2-test. The calculation of attention scores reveals that participants find it harder to concentrate during focused activities in uniform lighting scenarios, and they find it harder to relax during rest sessions in concentrated lighting scenarios. Regarding subjective indicators, mixed lighting is preferred for environmental illumination, and participants report that their eyes are less likely to feel dry or strained. |
| 參考文獻 |
[1] S. Nakamura, M. Senoh, and T. Mukai. P-GaN/N-InGaN/N-GaN doubleheterostructure blue-light-emitting diodes. Japanese Journal of Applied Physics, 32(Part 2, No.1A/B):L8–L11, 1993.
[2] H. R. Taylor et al. The long-term effects of visible light on the eye. Archives of Ophthalmology, 110(1):99–104, 1992.
[3] K. E. West et al. Blue light from light-emitting diodes elicits a dose dependent suppression of melatonin in humans. Journal of Applied Physiology, 110(3):619–626, 2011.
[4] W. J. M. van Bommel. Non-visual biological effect of lighting and the practical meaning for lighting for work. Applied Ergonomics, 37(4):461–466, 2006.
[5] W. J. M. van Bommel and G. J. van den Beld. Lighting for work: a review of visual and biological effects. Lighting Research and Technology, 36(4):255– 266, 2004.
[6] CNS 12112 中華民國國家標準. 室內工作場所照明. 經濟部標準檢驗局, 2012.
[7] Koninklijke Philips Electronics N.V., Feel good, learn better with SchoolVision, 2011.
[8] M. S. Mott et al. Illuminating the effects of dynamic lighting on student learning. SAGE Open, 2, 2012.
[9] I. Hirotake et al. Intellectual productivity under task ambient lighting. Lighting Research and Technology, 50, 2016.
[10] Choi, K., & suk, H. (2016). Dynamic Lighting System for the Learning Environment: Performance of Elementary Students. OPTICS EXPRESS A907, 24(10).
[11] Candra, H., Setyaningsih, E., Pragantha, J., & Chai, R. (2019). Enhancing Student’s Learning Experience in the Classroom Using Lighting Stimulation. International Journal of Innovation, Creativity and Change., 10(7).
[12] J.-H. Chu. CHAPTER1 認識色彩. Source: https://reurl.cc/Wd2Vge.
[13] J. R. Wilson and E. N. Corlett. Evaluation of Human Work, 2nd Edition. Taylor and Francis, 1995.
[14] H. Yoshitake. Relations between the symptoms and the feeling of fatigue. Ergonomics, 14(1):175–186, 1971.
[15] R. Likert. A technique for the measurement of attitudes. Archives of psychology , 1932.
[16] M. A. Robinson. Using multi-item psychometric scales for research and practice in human resource management. Human Resource Management, 57(3):739–750, 2018.
[17] S. Mack et al. Principles of Neural Science, Fifth Edition. McGraw-Hill Education, 2013.
[18] H. H. Suzana. The human brain in numbers: a linearly scaled-up primate brain. Frontiers in Human Neuroscience, 3:31, 2009.
[19] Human EEG with prominent alpha rhythm. Source: https://reurl.cc/QdvOoZ.
[20] A. M. Feyissa, W. O. Tatum. Adult EEG. Handbook clin neurol, 160:103-124, 2019
[21] H. Marzbani, H. R. Marateb, and M. Mansourian. Methodological note: Neurofeedback: A comprehensive review on system design, methodology and clinical applications. Basic and Clinical Neuroscience Journal, 7:143–158, 2016.
[22] G. Buzs´aki. Rhythms of the Brain. Oxford ; New York : Oxford University Press, 2006.
[23] B. McDermott et al. Gamma band neural stimulation in humans and the promise of a new modality to prevent and treat Alzheimer’s disease. Journal of Alzheimer’s Disease, 65(2):363–392, 2018.
[24] A. B. Usakli. Improvement of EEG signal acquisition: An electrical aspect for state of the art of front end. Computational Intelligence and Neuroscience, 2010, 2009.
[25] G. H. Klem et al. The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. Electroencephalography and clinical neurophysiology. Supplement, 52:3–6, 1999.
[26] International 10-20 system for EEG. Source: https://reurl.cc/lVxMOA.
[27] K. A. Carlson. An Introduction to Statistics: An Active Learning Approach. SAGE Publications, 2016.
[28] Reader’s Digest Editors. Can You Spot the Difference in These 10 Pictures? Source: https://reurl.cc/r88xnr.
[29] 陳奕傑，「室內照明情境下之靜態工作專注力評估」，國立中央大學，碩士論文，民國 109 年。
[30] MindDuo 2 親子共讀護眼檯燈Source: https://www.benq.com/zh-tw/lighting/parenting-reading-lamp/mindduo-2.html
[31] Aora 智能吸頂燈Source: https://www.benq.com/zh-tw/lighting/ceiling-lamp/aora.html
[32] NeuroSky. MindWave Mobile: User Guide, 2015.
[33] MindWave mobile. Source: https://www.me100fun.com.hk/products/neurosky-mindwave-mobile-2.
[34] 國軍智力測驗Source: https://www.kfsh.hc.edu.tw/uploads/article/3511/20190514165816.pdf
[35] https://en.wikipedia.org/wiki/D2_Test_of_Attention
[36] N. E. Huang et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 454:903–995, 1998.
[37] Mr. Opengate. Time Series Analysis - Introduction to Stationary Time Series. Source: https://reurl.cc/ZO6zo3.
[38] 陳佑榮，「應用希爾伯特黃轉換以C語言環境開發腦機介面訊號處理」，國立中央大學，碩士論文，民國104年。
[39] 洪暉程，「總體經驗模態分解法(EEMD)結合自回歸(AR)模型在旋轉機械之元件鬆脫故障診斷之應用」，國立中央大學，碩士論文，民國97年。 |
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