Shahed University

EEG signal analysis during Ishihara’s test in subjects with normal vision and color vision deficiency

Ali Ekhlasi | Hessam Ahmadi | Amir Molavi | Mohammad Saadat Nia | Ali Motie-Nasrabadi

URL :   http://research.shahed.ac.ir/WSR/WebPages/Report/PaperView.aspx?PaperID=158479
Date :  2021/01/29
Publish in :    Biomedical Physics & Engineering Express
DOI :  https://doi.org/https://doi.org/10.1088/2057-1976/abdbbc
Link :  http://dx.doi.org/https://doi.org/10.1088/2057-1976/abdbbc
Keywords : EEG signal Processing, Color Vision Deficiency, Ishihara Test, Classification,Frequency Features.

Abstract :
Color Vision Deficiency (CVD) is one of the most common types of vision deficiency. People with CVD have difficulty seeing color spectra depending on what types of retina photoreceptors are impaired. In this paper, the Ishihara test with 38 plates was used to examine the Electroencephalogram (EEG) of ten subjects with CVD plus ten healthy individuals. The recording was performed according to the 10–20 international system. The C-based software was programmed so that subjects could select the number or path in each test plate in the software options while recording EEG. Frequency features in different frequency bands were extracted from the EEG signals of the two groups during the Ishihara test. Statistically significant differences (P 0.05) between features were assessed by independent samples t-test with False Discovery Rate (FDR) correction. Also, the K-nearest neighbor classifier (KNN) was used to classify the two groups. The results revealed that the most significant difference between the two groups in the Ishihara test images occurred for the electrodes located in the right temporoparietal areas (P4 and T6) of the brain in the Delta, Theta, Beta1, and Beta2 frequency bands. The KNN classifier, using the signals that reported the greatest statistical difference between the two groups, showed that the two groups were distinguishable with 85.2 accuracy. In this way, images from the Ishihara test that would provide the most accurate classification were identified. In conclusion, this research provided new insights into EEG signals of subjects with CVD and healthy subjects based on the Ishihara color vision test.