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A mathematical approach to assess the ability of light filters to improve color discriminability of color vision deficient persons.

ABSTRACT: Color vision deficiency (CVD) is a frequent condition that alters color perception to such an extent that many people encounter serious difficulties on their everyday lives. In this work, we present a strategy to analyze the effectiveness of light filters aimed to improve color discriminability of persons with CVD. The calculations are based on a simple model of color discrimination which has been successfully applied to several animal species. We first tested the calculations on three well-known commercial lenses designed for persons with CVD. In agreement with results of clinical studies, the calculations show that the highly colored lenses (VINO® and X-Chrom®) enhance chromaticity contrasts between problematic colors, whereas the more neutral Enchroma® do not provide any benefit. Also, we predict that two light filters proposed in recent works for novel lenses would not improve the performance of the commercial ones. Since the mathematical approach presented in this work enables predictive filter assessment, it opens the door to future research on the design of more effective lenses to improve color discriminability of persons with CVD. The calculations allow for large-scale screening of numerous light filters and different colored stimuli, CVD conditions, light sources, etc.

SUBMITTER: Gonzalez Bardeci N

PROVIDER: S-EPMC8482439 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundMobile health (mHealth) apps using novel visual mapping assistive technology can allow users to develop personalized maps that aid people living with cognitive impairment in the recall of steps needed to independently complete activities of daily living (ADLs), such as bathing, toileting, and dressing.ObjectiveThis study aims to determine the feasibility and preliminary impact of an mHealth assistive technology app providing guidance to aid individuals living with cognitive impairment in the recall of steps to independently complete ADLs.MethodsA total of 14 Veterans (mean age 65 SD 9.5 years; 14/14, 100% male; 10/14, 71.4% Black) and 8 non-Veterans (mean age 78, SD 10.3 years; 5/8, 62.5% male; 8/8, 100% Black) were recruited and enrolled from the Department of Veterans Affairs (VA) and non-VA cognitive care clinics. A visual mapping software program, MapHabit, was used to generate a series of personalized visual map templates focused on ADLs created within the MapHabit app. The visual maps were accessed through a tablet device. A 19-item exit questionnaire was administered to the participants to assess perceived improvement in their functional ability after using the MapHabit system for 3 months.ResultsA total of 13 (93%) VA clinic participants and 8 (100%) non-VA clinic participants completed the 3-month study. Baseline cognitive testing indicated impaired to significantly impaired cognitive function. After 3 months of using the MapHabit system, VA clinic participants reported perceived improvement in social engagement (P=.01) and performance of ADLs (P=.05) compared to the baseline, whereas non-VA clinic participants reported improvements in the performance of ADLs (P=.02), mood (P=.04), social engagement (P=.02), and memory (P=.02). All study participants reported they would recommend the MapHabit system to a colleague, and 85% (11/14) of VA and 100% (8/8) of non-VA clinic participants reported a willingness to participate in a future study.ConclusionsOlder VA and non-VA clinic participants with cognitive impairment were willing to use an mHealth app to assist with the completion of ADLs, and they reported positive preliminary effects. A larger study is warranted to assess the efficacy in the setting of a randomized controlled trial.

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A mathematical approach to assess the ability of light filters to improve color discriminability of color vision deficient persons.

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