- 學位論文
EEG量測視覺疲勞及心智負荷之可用性評估
The applicability of EEG in measuring visual fatigue and mental workload
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摘要
腦電波圖(Electroencephalography, EEG)在臨床上常用來量測人類各種認知及行為反應。本研究希望透過實驗來了解EEG頻域功率及平均振幅指標，和視覺疲勞及心智負荷間的關係，進而探討EEG指標在量測視覺疲勞及心智負荷的可用性。本研究共分為兩階段實驗進行，第一階段實驗，是透過比較EEG頻域功率指標和常用的視覺疲勞指標--近點調節值(NPA)、閃光融合閾值(CFF)及主觀疲勞問卷間之關係，來了解EEG頻域功率指標在量測視覺疲勞的可用性。共20位男性受試者(平均20.4歲,SD=1.46)參與實驗，實驗作業為120分鐘之模擬賽車遊戲。結果顯示EEG頻域功率指標可有效反應視覺疲勞程度的變化，且其敏感度比主觀視覺疲勞指標更佳。其中EEG β 和α分別適用於短時間及長時間視覺疲勞的量測。整體而言，EEG β/α為第一階段實驗中最佳的視覺疲勞量測指標。 第二階段實驗旨在評估EEG平均振幅指標用於量測操作多工作業時之心智負荷的可用性。共30 位男性受試者參與3段各10分鐘的模擬飛行(MATB)心智負荷實驗(有3個不同的心智負荷水準)，受測者被要求維持穩定保持最佳操作正確性之策略。實驗中共量測10種EEG指標(分別從大腦枕葉部O1-O2及額葉部F4-C4取得α, β, θ, α/θ, 和θ/β 等平均振幅值做為指標)，及12種心率變異(HRV)指標，並以NASA-TLX (Task Load index) 及RSME (Rating Scale on Mental Effort)等主觀問卷記錄主觀心智負荷的變化，進而以變異數分析及相關性分析評估EEG平均振幅指標對心智負荷水準變化之敏感度。研究結果顯示EEG θ, α/θ (F4-C4) 和HRV指標中的SDNN, VLF, LF, %HF, LF/HF等指標可有效反應心智負荷的變化，而EEG α/θ (F4-C4) 以及LF/HF為本研究中最敏感的心智負荷量測指標。其中LF/HF和本實驗中其他生理指標間有很高的關聯性，而EEG α/θ (F4-C4)則和本實驗中主觀心智負荷指標有十分顯著的關聯性。此外，本研究也發現操作策略的確會影響EEG α (F4-C4) 和HF等指標的量測敏感性。 以上結果說明了EEG頻域功率及平均振幅指標可分別有效量測視覺疲勞及心智負荷，但使用上仍需注意實驗作業特性以及操作策略設定，這些條件將影響EEG指標使用的可靠性。上開結果可供未來使用EEG評估駕駛安全警示或航空器操作環境安全之參考。
並列摘要
EEG is widely used in cognitive and behavioral research. This study evaluates the effectiveness of using the EEG power and mean amplitude indices to measure visual fatigue and mental workload. Two-stage experiments are included in this study. In the first experiment, three common visual fatigue measures, critical-flicker fusion (CFF), near-point accommodation (NPA) and subjective eye-fatigue rating (questionnaire) were used to compare with the EEG power index. The subjects were 20 men with a mean age of 20.4 years (SD=1.46). The experimental task was a 120 min car-racing video game. Results indicated that the EEG power indices were valid as a visual fatigue measure and the sensitivity was higher than the subjective measure. The EEG β and EEG α power indices were effective for measuring visual fatigue in short and long-duration tasks, respectively. The EEG β/α was the most effective power index for the visual fatigue measure in this experiment. The second experiment aimed to identify EEG mean amplitude indices that can accurately monitor mental workload while subjects performed multiple tasks with the strategy of maintaining stable performance and maximizing accuracy. 30 male subjects completed three 10 min multitasks with 3 workload levels. 25 mental workload measures including 10 EEG mean amplitude indices (α, β, θ, α/θ, θ/β from O1-O2 and F4-C4), heart rate, 12 heart rate variability (HRV) indices, and 2 subjective measures data were collected. One-way ANOVA with repeated measures, Pearson correlation and Duncan post-hoc test were employed to observe index sensitivity. The results showed that EEG θ, α/θ (F4-C4), and SDNN, VLF, LF, %HF, LF/HF are sensitive to differentiated high workload levels. EEG α/θ (F4-C4) and LF/HF are most effective for monitoring high mental workload. EEG α/θ (F4-C4) showed strong correlations with subjective measures across different mental workload levels. Additionally, we found the operation strategy would affect the sensitivity of EEG α (F4-C4) and HF. These findings identified the EEG measure are valid in measuring visual fatigue and mental workload. Besides, the task characteristic and operation strategy might affect the validity of EEG indices. The results, furthermore, can be applied to enhance the safety, health, and comfort of the users involved in heavy visual requirement and mental workload tasks. Keywords: EEG, visual fatigue, mental workload, physiological index, subjective rating.
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