# EEG-Based Methods for Diagnosing Color Vision Deficiency: A Comprehensive Review
## 1 Introduction  
Color vision deficiency (CVD) is one of the most common vision disorders. It is the inability to differentiate between colors and shades under typical lighting conditions [1]. Globally, CVD affects approximately \(1\) in 200 women and \(1\) in 12 men [2]. This disparity arises because CVD can be inherited through the X chromosome. Men possess one X chromosome, while women possess two. For women to have CVD, both X chromosomes (inherited from the mother and father) must carry the CVD genes, which is rare. Conversely, men inherit one X chromosome inherited from their mother, making it more common for them to have the CVD gene [3; 4; 5]. Prevalence rates vary among populations. Reports indicate prevalence rates of 3.28% in Saudi Arabia, 8.4% in European populations, 7.3% in Turkey, 8.7% in India and Jordan, and 4% to 6.5% in China [6; 7; 8; 9; 10]. These variations are influenced by genetic factors, as studies have shown that gene frequencies differ between populations [10]. Other contributing factors include environmental influences, such as medication reactions and exposure to chemicals [11]. Moreover, consanguineous marriages, which are more common in Muslim populations, may increase the prevalence of genetic disorders, including CVD [12]. Although CVD impacts individuals across various ethnic and geographic demographics, a significant proportion of cases remain undetected or unacknowledged during the early stages of life [1]. This may occur due to a lack of appropriate and precise diagnostic techniques targeting this disorder. CVD usually affects people in their daily lives. Research has shown that individuals with CVD may lack awareness, and students' academic performance can be negatively affected by it [13; 14]. However, early diagnosis of CVD can help individuals manage the condition and plan their future career paths. Early detection of CVD is crucial, as it allows for timely intervention and support for affected individuals, particularly in educational and occupational settings. Early detection enables individuals to address potential academic challenges and optimize their learning experiences. Certain occupational environments require the ability to discriminate colors, such as aviation, electrical engineering, and graphic design. Therefore, earlydetection of CVD ensures that individuals can make informed career choices and avoid limitations [2; 15]. Furthermore, recognizing CVD early may also allow for the identification of other vision diseases that may be linked to it, such as amblyopia and refractive errors [9]. Overall, the early detection of CVD improves the well-being and quality of life of those affected. Currently, none of the available tests can fully and accurately evaluate color vision [16; 17]. The most commonly used methods to assess color vision include the widely used Ishihara test, the Farnsworth-Munsell (FM) 100 Test, and the Anomaloscope [16; 17; 18]. Although these methods can assess color vision, they have limitations that may affect their effectiveness. One such limitation is that these tests require a behavioral response, making it impossible for individuals with locked-in syndrome to use these tests due to their physical and communication limitations. Locked-in syndrome is defined as quadriplegia resulting from damage to the brainstem, rendering individuals unable to move except for their eye movements [19; 20; 21]. Additionally, another issue is that these tests are subjective and cannot accurately gauge how the user perceives variations in hue. Furthermore, considerable training is required before taking the test, which is not feasible for many people with neurological impairments. Finally, because some users can memorize the answers to the questions, the outcomes of these examinations may be manipulated. These limitations highlight the importance of finding alternative ways to diagnose CVD efficiently. In recent years, the utilization of Brain-Computer Interfaces (BCIs) has proven effective in various medical applications.