Computerized Full-Color Assessment for Distinguishing Color Vision Deficiency

用于区分色觉缺陷的计算机化全彩评估

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Abstract

Background/Objectives: Current methods for diagnosing color vision deficiency (CVD) generally fall into two categories: computer-based tests that lack full-color lighting and non-computer-based tests that provide full-color lighting. Most of these approaches face several limitations, including inaccurate illumination of test samples, inconsistent test durations, learning effects, and the need for highly skilled operators. Methods: To address these limitations, this study introduces the Computerized Full-Color Assessment (CFCA) method, which employs a full-color light generation system based on 16 color spectra selected from the classical Farnsworth D-15 (D-15) test. In the CFCA method, each pair of colors generated by the system was presented under software control, and participants indicated within three seconds whether the colors were different. The total test duration was limited to 5 min. The method was validated using 10 normal trichromats and 11 patients with CVDs. Results: Results obtained from the CFCA were compared with those from the classical D-15 test using quantitative parameters, including confusion angle (CA) and confusion index (CI). Correlations between the two methods were analyzed. The p-values for CA and CI are 0.688 and 0.587, respectively, and the correlation coefficients are 0.821 for CA and 0.884 for CI, indicating a strong and statistically significant correlation. Conclusions: The CFCA method provides an accurate, convenient, and efficient tool for diagnosing CVD, with particular advantages for use in young children. It enables an expanded range of color choices beyond the 16 discs of the D-15 test and allows for the generation of individualized visual spectra, which can be applied in the design of customized color-vision-correcting glasses.

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