室內照明情境下之靜態工作專注力評估;Evaluation of Static Work Attention Under Indoor Lighting Environments

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题名:	室內照明情境下之靜態工作專注力評估;Evaluation of Static Work Attention Under Indoor Lighting Environments
作者:	陳奕傑;Chen, I-Chieh
贡献者:	光電科學與工程學系
关键词:	照明;腦電圖;經驗模態分解法;邊際頻譜;頻帶功率;機率密度函數;接收者操作特徵曲線;lighting;EEG;empirical mode decomposition (EMD);marginal spectrum;band power;probability density function (PDF);ROC curve
日期:	2020-08-20
上传时间:	2020-09-02 15:46:06 (UTC+8)
出版者:	國立中央大學
摘要:	在21世紀初照明實質影響生理回饋的研究被提出後，注重燈具色溫、光譜演色性的議題便大量浮上檯面，因此，探討不同照明因子對使用者生理與精神狀況的影響成為人因工程中相當重要的一部份。本研究係以辦公室環境為實驗空間，以可調變的平板燈營造均勻且可自由控制的照明情境。實驗以招募受試者進行模擬辦公工作的靜態文書作業為主，作業內容與問卷評估等流程沿用先前團隊人員所設計之成果，惟生理因素的客觀評估工具本研究新增了生理回饋儀來進行腦波量測，結合既有之工具設計新的人因評估流程以及各項評估指標。實驗主要利用生理回饋儀、LED 可調式平板燈、閃光融合儀、評估問卷等工具。生理回饋儀負責量測受試者於平板燈調控情境下的腦波訊號，匯入Matlab 軟體進行包含經驗模態分解法(Empirical mode decomposition, EMD)、傅立葉轉換(Fourier transform, FT) 及希爾伯特－黃轉換(Hilbert-Huang transform, HHT)、機率密度函數(Probability density function, PDF)、接收者操作特徵曲線(Receiver operating characteristic curve, ROC curve) 等運算，最後則將接收者操作特徵曲線的曲線下面積(Area under the curve, AUC) 依情境排列作為客觀指標；以問卷評估所得之評分，亦依情境排列後成為主觀指標。主客觀指標將分別匯入SPSS 軟體進行變異數分析，檢視指標於12 種情境間是否具顯著差異，以進一步探討主客觀指標的情境分布狀況。實驗結果在客觀指標方面，受試者在高色溫低照度時較高；主觀指標方面，受試者評分則較青睞高色溫高照度。但在視覺舒適度的評估上，客觀結果與主觀結果則可相呼應，以3840 K 和750 lux 的照明情境下為最佳。;After the proposal of the study of how lighting influencing humans’ biofeedback at the beginning of 21th century, topics about color temperature, power spectral density, or color rendering are becoming more and more popular. Therefore, research on how lighting factors affecting users’ physiological situations is absolutely an important part in human-factor engineering. This study takes the office environment as the experimental area. Several controllable and uniform lighting setups are designed by using the LED flat panel lights. The experiments recruit participants and request them to complete some documental works and questionnaires, which are referenced from the results before. The objective tool added in this study is the biofeedback device, which could measure human electroencephalography (EEG). The new experimental flow is based on the combination of EEG measurement and other evaluation indices. The experimental materials include the biofeedback device, the controllable flat panel lights, the critical flicker fusion frequency (CFF) instrument, and the self-evaluation questionnaires. The biofeedback device could measure the users’ EEG signals. Then the signals are collected into Matlab and going through empirical mode decomposition (EMD), Fourier transform (FT), Hilbert-Huang transform (HHT), probability density function (PDF), and receiver operating characteristic curve (ROC curve) analysis. The area under curves (AUCs) are calculated and arranged to become the objective indices. On the other hand, the scores of the questionnaires are also arranged in order of the lighting environments, and then become the subjective indices. Both of them are collected into SPSS for the twoway analysis of variance (ANOVA) to check if there is any significance among the 12 lighting environments. Results show that in the objective part, the area under curves have great performance in higher color temperature and lower illuminance. According to the subjective indices, participants prefer both higher color temperature and illuminance. Yet according to the evaluation of visual comfort, both the objective and subjective measures have the best result in the lighting environment of 3840 K and 750 lux.
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