Back to articles
Article
Volume: 35 | Article ID: HVEI-253
Image
A multichannel LED-based lighting approach to improve color discrimination for low vision people
  DOI :  10.2352/EI.2023.35.10.HVEI-253  Published OnlineJanuary 2023
Abstract
Abstract

The population of low vision people increases continuously with the acceleration of aging society. As reported by WHO, most of this population is over the age of 50 years and 81% were not concerned by any visual problem before. A visual deficiency can dramatically affect the quality of life and challenge the preservation of a safe independent existence. This study presents a LED-based lighting approach to assist people facing an age-related visual impairment. The research procedure is based on psychophysical experiments consisting in the ordering of standard color samples. Volunteers wearing low vision simulation goggles performed such an ordering under different illumination conditions produced by a 24-channel multispectral lighting system. A filtering technique using color rendering indices coupled with color measurements allowed to objectively determine the lighting conditions providing the best scores in terms of color discrimination. Experimental results were used to combine 3 channels to produce white light inducing a stronger color perception in a low vision context than white LEDs nowadays available for general lighting. Even if further studies will be required, these first results give hope for the design of smart lighting devices that adapt to the visual needs of the visually impaired.

Subject Areas :
Views 101
Downloads 39
 articleview.views 101
 articleview.downloads 39
  Cite this article 

Linna Yang, Éric Dinet, Pichayada Katemake, Alain Trémeau, Philippe Colantoni, "A multichannel LED-based lighting approach to improve color discrimination for low vision peoplein Electronic Imaging,  2023,  pp 253-1 - 253-11,  https://doi.org/10.2352/EI.2023.35.10.HVEI-253

 Copy citation
  Copyright statement 
Copyright © 2023, Society for Imaging Science and Technology 2023
ei
Electronic Imaging
2470-1173
2470-1173
Society for Imaging Science and Technology
IS&T 7003 Kilworth Lane, Springfield, VA 22151 USA