| DC 欄位 |
值 |
語言 |
| DC.contributor | 光電科學與工程學系 | zh_TW |
| DC.creator | 柯景瀚 | zh_TW |
| DC.creator | Jing-Han Ke | en_US |
| dc.date.accessioned | 2022-1-26T07:39:07Z | |
| dc.date.available | 2022-1-26T07:39:07Z | |
| dc.date.issued | 2022 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=108226012 | |
| dc.contributor.department | 光電科學與工程學系 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 本研究以模擬辦公室內環境為實驗空間，分別分析在「噪音環境」下 進行專注度遊戲與在「不同晝夜節律刺激值的照明環境」下進行閱讀測驗 之腦波資訊，進一步探討噪音的干擾與照明情境中不同晝夜節律刺激值 (Circadian Stimulus, CS)的變化，對受試者的專注度有何影響。本研究將利 用先前研究團隊原有的實驗設計所收集的腦波資料，來定義出新的客觀專 注度相關指標，將該指標進一步轉換為專注度成績，分別探討工作與休息 時之專注度成績差異。
在噪音環境影響專注度的實驗中，使用到筆記型電腦讓受試者進行記 憶力相關的專注度遊戲、三件式音箱播放工地噪音模擬施工之噪音情境、 Neurosky 腦波儀負責量測受試者受到噪音干擾情境下玩遊戲之腦波數據。 在不同晝夜節律刺激值照明環境影響專注度的實驗中使用到光譜可調式光 源箱設計不同色溫或不同晝夜節律刺激值之照明環境，藉此來對受試者的 生心理產生影響並提升精神狀況、實驗中的閱讀測驗內容為歷年指考考 題、Neurosky 腦波儀為負責記錄受試者腦波數據，並利用希爾伯特-黃轉 換(Hilbert-Huang transform, HHT)執行進一步主客觀數據分析，以此來建立 照明人因評估。
耳機型腦波儀記錄受試者於不同實驗情境下的腦波訊號，利用 MATLAB 軟體進行數據分析，其中包含希爾伯特-黃轉換、機率密度函數 (Probability density function, PDF)以及接收者操作特徵曲線(Receiver operating characteristic curve, ROC curve)、由接收者操作特徵曲線計算曲線
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下面積(Area under the curve, AUC)當作客觀指標之一，除了使用接收者操 作特徵曲線進行分析外，也使用經由希爾伯特-黃轉換後所得之不同頻段的 頻帶功率作為特徵值，以支持向量機(Support vector machine, SVM)進行專 注與休息狀態之分類。
研究結果顯示在本論文中所開發之專注度相關指標能夠有效率的區分 不同環境中受試者的專注與休息狀態，受試者們在專注與休息狀態下之專 注度成績經由成對 t 檢定有著顯著的差異;在有無環境噪音之實驗中並非 所有受試者都受噪音影響;在相同色溫而 CS 值為 0.25 、 0.35 、 0.45 的 照明環境中進行閱讀測驗，專注度成績最高之情境為 CS 值為 0.45 時;而 在同 CS 值不同色溫的照明環境中進行閱讀測驗，受試者的專注度成績沒 有顯著的差異。 | zh_TW |
| dc.description.abstract | In this study, we use a simulated office environment as the experimental space, and analyze the brainwave signals of the memory-related games under ＂different sound situations＂ and of the reading tests under ＂different lighting situations＂. The aim is to explore the interference of different sounds or different circadian stimulus (CS) of the lighting situations on the concentration of participants. We utilize the experimental design of previous studies in our research group and define a new concentration index, which will be converted into the concentration score for comparing the concentration levels of the working and resting states.
In the experiment of ＂different sound situations＂, we use a laptop for participants to play memory-related games, there-piece speakers to play prerecorded noises of a construction site, and a Neurosky brainwave measuring device to acquire the brainwave data of participants. In the experiment of ＂different lighting situations＂, two spectrum adjustable light sources are used to design the lighting situations with different correlated color temperature (CCT) or CS. The questions in the reading tests are from the college entrance examinations of the past years. The Neurosky device is again responsible for measuring the brainwave data of participants.
The recorded brainwave signals undergo several processes in the MATLAB environment, including Hilbert-Huang transform (HHT), probability density function (PDF), receiver operating characteristic curve (ROC curve), and finally the area under the curve (AUC) as one of the objective index. In addition to
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using the ROC curve for data analysis, we also use the support vector machine (SVM) for binary classifications of the working and resting states.
The results show that the concentration index developed in this study can effectively distinguish the concentration and resting states of participants in different situations. The concentration scores of participants in the attentive and resting states have a significant difference by the paired t test. In the sound experiment, not all participants are affected by the noise. In the lighting experiment with the same CCT, among the tested CS values of 0.25, 0.35, and 0.45, the participants have the highest average concentration score when the CS value is 0.45. In the lighting experiment with the same CS but different CCTs, the concentration scores of participants have no significant differences between lighting situations. | en_US |
| DC.subject | 腦電圖 | zh_TW |
| DC.subject | 經驗模態分解法 | zh_TW |
| DC.subject | 希爾伯特轉換 | zh_TW |
| DC.subject | 機率密度函數 | zh_TW |
| DC.subject | 接收者操作特徵曲線 | zh_TW |
| DC.subject | 專注度指標 | zh_TW |
| DC.subject | EEG | en_US |
| DC.subject | empirical mode decomposition | en_US |
| DC.subject | Hilbert transform | en_US |
| DC.subject | probability density function | en_US |
| DC.subject | receiver operating characteristic curve | en_US |
| DC.subject | concentration index | en_US |
| DC.title | 不同聲音或照明情境下室內靜態工作之專注程度指標開發 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Development of concentration index for indoor static work with different sound or lighting situation | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |