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首页> 外文期刊>SID International Symposium: Digest of Technology Papers >Visual Fatigue Assessment and Modeling Based on ECG and EOG Caused by 2D and 3D Displays
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Visual Fatigue Assessment and Modeling Based on ECG and EOG Caused by 2D and 3D Displays

机译:基于2D和3D显示器的ECG和EOG的视觉疲劳评估和建模

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Three-dimensional (3D) displays become more and more popular in many fields, because they can provide amazing visual effects. However, visual fatigue as one of the critical factors has seriously impeded the wide range of applications of 3D technology. Electrocardiograph (ECG) and electrooculogram (EOG) have been widely used for monitoring visual fatigue. In this paper, one more objective and effective visual fatigue evaluation model is proposed. Subjective scores (SS), heart rates (HR), blink frequency (BF), Sympathetic activity, Vagal activity, Sympathetic-vagal ratio (a measure of autonomic balance), Average of NN intervals (NN-MEAN) and Standard deviation of NN intervals (SDNN) of all subjects were collected to analyze the change of visual fatigue during the continuous viewing 3D/2D movie. The results showed that SS, HR, BF, Sympathetic activity and SDNN all increase with visual fatigue while NN-MEAN and Vagal activity decrease. As shown by the result of subjective scoring, the visual fatigue has an overall trend of increasing when viewing both 2D and 3D videos and it is higher in 3D condition than in 2D. Based on the results above, two models were built to predict visual fatigue from above indicates during continuous viewing 2D and 3D video processes respectively. The performance of the models makes a good prediction of visual fatigue.
机译:三维(3D)显示器在许多领域中越来越受欢迎,因为它们可以提供惊人的视觉效果。但是,视觉疲劳作为关键因素之一严重阻碍了3D技术的广泛应用。心电图仪(ECG)和眼电图仪(EOG)已广泛用于监视视觉疲劳。本文提出了一种更加客观有效的视觉疲劳评估模型。主观评分(SS),心率(HR),眨眼频率(BF),交感神经活动,迷走神经活动,交感神经迷走神经比率(一种自主神经平衡的量度),NN间隔的平均值(NN-MEAN)和NN的标准差收集所有对象的时间间隔(SDNN),以分析连续观看3D / 2D电影期间视觉疲劳的变化。结果表明,SS,HR,BF,交感神经活动和SDNN均随着视觉疲劳而增加,而NN-MEAN和迷走神经活动减少。如主观评分的结果所示,在观看2D和3D视频时,视觉疲劳总体上呈上升趋势,并且在3D条件下比2D更高。基于以上结果,建立了两个模型来分别预测连续观看2D和3D视频过程期间从上方指示的视觉疲劳。模型的性能可以很好地预测视觉疲劳。

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