Optical health analysis of visual comfort for bright screen display based on back propagation neural network

Kun Wang, Chun Heng Ho, Chunpeng Tian, Yan Zong

研究成果: Article同行評審

1 引文 斯高帕斯(Scopus)


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.

期刊Computer Methods and Programs in Biomedicine
出版狀態Published - 2020 11月

All Science Journal Classification (ASJC) codes

  • 軟體
  • 電腦科學應用
  • 健康資訊學


深入研究「Optical health analysis of visual comfort for bright screen display based on back propagation neural network」主題。共同形成了獨特的指紋。