作者：刘国忠1, 张立伟2, 高洁1, 孟皓1, 李萍3
作者单位：1. 北京信息科技大学仪器科学与光电工程学院，北京 100192;
2. 北京航空航天大学生物与医学工程学院，北京 100083;
3. 北京信息科技大学自动化学院，北京 100192
关键词：图像清晰度;评价模型;EEG;ERP;指数拟合模型
摘要：
脑电信号能够反映大脑的认知状态，建立一套基于脑电信号的图像清晰度评估模型来评估是否醉酒等特殊状态具有重要的现实意义。采集10名健康被试者对5种不同模糊等级图像的双刺激连续质量标度量表和脑电数据，结果确定大脑皮层中的中-顶区为特征脑区，并利用指数拟合函数对量表和特征脑区的P300波分别与图像模糊等级建立评价关系模型。结果还发现受试者的脑电信号在饮酒状态下没有明显的P300成分。结果表明基于P300成分的脑电信号可以用来评价图片的清晰度，并可应用于关键工作岗位从业人员的饮酒等特殊状态的监测。
Study on the application of P300 EEG signal in image definition evaluation
LIU Guozhong1, ZHANG Liwei2, GAO Jie1, MENG Hao1, LI Ping3
1. School of Instrument Science and Opto-electronics Engineering, Beijing Information Science & Technology University, Beijing 100192, China;
2. School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, China;
3. School of Automation, Beijing Information Science & Technology University, Beijing 100192, China
Abstract: EEG can reflect the cognitive state of the brain, so it is important practical significance to establish an image definition evaluation model based on EEG for evaluating whether special cognitive states such as drunkenness. The dual-stimulus continuous quality scales and EEG data of 10 healthy subjects were collected from five fuzzy degree of images. The results showed that the central-parietal region of the cerebral cortex was the feature region. The scale and the P300 wave of the feature region respectively establishes an evaluation model with the image fuzzy degree by using the exponential fitting function. The results also showed that there was no significant P300 in subjects EEG in the drinking state. The results indicated that P300 component of EEG can be used to evaluate the image definition, and can be applied to the monitoring of special status of employees in key jobs, such as drinking.
Keywords: image definition;evaluation model;EEG;ERP;exponentially fitted model
2020, 46(3):52-58 收稿日期: 2018-12-17;收到修改稿日期: 2019-02-04
基金项目: 北京市自然科学基金资助项目（7172035）
作者简介: 刘国忠(1966-),男,山西平遥县人,教授,博士,研究方向为精密测量技术、脑-机接口等
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