研究生: |
陳麒元 |
---|---|
論文名稱: |
利用生理訊號評估心智負荷之研究 |
指導教授: | 王茂駿 |
口試委員: |
石裕川
林志隆 |
學位類別: |
碩士 Master |
系所名稱: |
工學院 - 工業工程與工程管理學系 Department of Industrial Engineering and Engineering Management |
論文出版年: | 2011 |
畢業學年度: | 99 |
語文別: | 中文 |
論文頁數: | 66 |
中文關鍵詞: | 心智負荷 、生理量度 、主觀量度 、腦波圖 、心電圖 |
外文關鍵詞: | mental workload, physiological measure, subjective measure, EEG, ECG |
相關次數: | 點閱:3 下載:0 |
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諸多研究顯示人員作業績效與心智負荷程度相關,過高的心智負荷易導致作業人員疲勞或逃避,過低的心智負荷則容易產生降低警戒的情形。若能即時掌控人員的心智負荷狀態、維持適當負荷程度,將能提升人員安全性、舒適度以及生產力。
本研究試圖藉由輕便設備及簡易生理訊號採集方式廣泛收集多種生理訊號,找出與心智負荷最為相關的生理指標,並檢視生理訊號的變化與主觀問卷分數的相關性。
30位平均年齡21.8歲男性受試者參與本研究之實驗,以NASA-MATB (Multi-Attribute Task Battery)作為實驗作業,並執行三種不同作業難度階段。每個實驗階段都會即時擷取生理訊號,並在每階段結束後進行主觀問卷填寫。客觀生理訊號共有額葉及枕葉EEG振幅、心搏率、時域心率變異、頻域心率變異等,主觀負荷量度量表則有NASA-TLX及RSME。
研究結果顯示,腦部額葉EEG之α/θ複合指標,以及ECG之頻域指標LF、LF/HF對於作業難度變化反應最為線性,適合當作心智負荷監控指標。而其中腦部額葉EEG之α/θ複合指標、頻域HRV之LF/HF對主觀問卷RSME及NASA-TLX的分數都具有顯著的相關。
本研究的研究結果將可運用於心智工作為主之工廠機台操作人員,使相關人員得以控制在適切的負荷狀態,保持作業績效、降低失誤及意外發生。
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