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The clinical assessment methods of detection of colour blindness are prone to subjective bias, human errors, and lack of consistency. Also, heterogeneous nature of vision deficiencies makes manual detection difficult. Hence, objective methods based on physiological signals can be used. Various studies have been undertaken to analyze the effect that colour perceived has on EEG signals and as a result can be extended to detection of colour blindness. The results of this survey indicate that there are significant differences produced in EEG signals due to changes in colour, as well as due to differences in colour perception. EEG signals also differ between healthy and colour vision deficient individuals, thereby providing a biomarker for detection. This biomarker can be exploited using machine learning algorithms for detection of colour-related vision deficiencies.