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| 基于眼动数据的视觉疲劳检测方法研究 |
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胡炜1,2, 赵小燕1,2, 陈泉1,2, 冯桂焕1,2, 骆斌1,2
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1.南京大学 软件学院, 江苏 南京 210093;2.计算机软件新技术国家重点实验室(南京大学), 江苏 南京 210023
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| 摘要: |
| 视觉疲劳的产生不仅会导致工作效率低下、视力降低，甚至可能导致很多意外伤害.如何简便、快速地检测视觉疲劳是亟需解决的课题.提出一种利用特殊字搜索并结合阅读任务来对视觉疲劳进行快速检测的方法.测试者需在所提供的阅读材料中通过扫视行为寻找出文内的特殊字符，同时完成相应的阅读理解任务.实验在Tobii X230眼动仪监测下完成.系统记录任务完成过程中的瞳孔直径比、兴趣域个数等眼动数据信息，并采用BP神经网络对用户的视觉疲劳状态进行判定.基于10位测试者的实验结果表明，分类精度达到了95.2%，证实了该方法的有效性. |
| 关键词: 眼动交互 视觉疲劳 特殊字 阅读理解 神经网络 |
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| 基金项目:国家自然科学基金（61100109) |
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| Visual Fatigue Detection Based on Eye Tracking Data |
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HU Wei1,2, ZHAO Xiao-Yan1,2, CHEN Quan1,2, FENG Gui-Huan1,2, LUO Bin1,2
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1.Software Institute, Nanjing University, Nanjing 210093, China;2.State Key Laboratory for Novel Software Technology(Nanjing University), Nanjing 210023, China
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| Abstract: |
| Visual fatigue cannot only lead to decreased productivity and vision, it might also bring various accidental injuries. How to detect visual fatigue in a simple and fast way is an urgent topic. This paper proposes a visual fatigue detection approach with the aid of special characters searching and reading tasks. Participants are required to locate these special characters from the reading materials through scanning, and at the same time complete the corresponding reading comprehension tasks. The experiment is conducted under the monitoring of Tobii X230 eye tracker. Eye tracking data, such as pupil diameter ratio, number of AOIs etc. are recorded. BP neural network is employed to determine the state of visual fatigue. The experimental results on 10 users show a classification accuracy of 95.2%, which confirms the effectiveness of the approach. |
| Key words: eye tracking interaction visual fatigue special character reading comprehension neural network |
