Background

The visual comfort of liquid crystal display (LCD) is the subjective evaluation of the user. It is a multi-dimensional and multi-factor problem, which is affected by the luminous characteristics of the LCD screen, the physiological factors of the user, and some other environmental factors.

Methods

Based on the theory of visual comfort under the guidance of ergonomics, this paper adopts a combination of objective measurement and subjective evaluation to obtain objective data such as blink frequency and pupil size changes, and subjective evaluation data on screen parameters. Correlation analysis was used to screen subjective and objective data, and an LCD visual comfort evaluation using the back propagation (BP) neural network was constructed with the aim of a concise evaluation of the LCD's own light-emitting characteristics, user's physiological factors, and environmental factors.

Results

After testing, the model can successfully predict the optimal visual level of the screen. After training, the relative error between the predicted value of visual comfort and the actual evaluation value is mostly within 10%. Based on this model, the display brightness and color temperature control system combined with the ambient light sensor can automatically adjust the brightness of the screen and the temperature of color parameters in correlation to user's gender, age, and ambient light changes to achieve the effect of improving visual comfort. Setting and user parameter adjustment provide a new method. The maximum adjustment error of the system after testing is 5.378%.

Conclusion

Our proposed technique can serve as a useful analysis platform for understanding and evaluating the visual comfort of the bright LCD screen at home or in the workplace, and enhancing optical health of humans.

中文翻译：

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基于反向传播神经网络的明亮屏幕视觉舒适度光学健康分析。

背景

液晶显示器（LCD）的视觉舒适度是用户的主观评价。这是一个多维和多因素的问题，受LCD屏幕的发光特性，用户的生理因素以及其他一些环境因素的影响。

方法

基于人机工程学的视觉舒适性理论，本文采用客观测量和主观评价相结合的方法，获得眨眼频率和瞳孔大小变化等客观数据，以及屏幕参数的主观评价数据。使用相关性分析筛选主观和客观数据，并构建了使用反向传播（BP）神经网络的LCD视觉舒适度评估，目的是简洁评估LCD自身的发光特性，用户的生理因素和环境因素。

结果

经过测试，该模型可以成功预测屏幕的最佳视觉水平。训练后，视觉舒适度的预测值与实际评估值之间的相对误差大部分在10％以内。基于此模型，显示亮度和色温控制系统与环境光传感器相结合，可以根据用户的性别，年龄和环境光的变化自动调整屏幕的亮度和颜色参数的温度，从而达到效果。改善视觉舒适度。设置和用户参数调整提供了一种新方法。经测试，系统最大调整误差为5.378％。

结论

我们提出的技术可作为有用的分析平台，用于了解和评估家庭或工作场所中明亮LCD屏幕的视觉舒适度，并增强人类的光学健康。