The relationship between mental performance and physiological factors in the field of human cognition is a topic of interest for researchers and scientists This experiment aimed to classify mental performance using eye data, specifically eye movement tracking data such as x and y coordinates, triggered eye characteristics, blink occurrences, and fixations. The data was processed, and 57 features were extracted and categorized into three groups. These features were used as input for six different classifiers, and the models' performance was evaluated. The findings consistently showed that using a Multi-layer Perceptron (MLP) classifier with all features from the three groups yielded the best results in terms of F1-scores and average accuracies

Хамуд Б. (науч. рук. Кашевник А.М.) AN APPROACH AND EVALUATION TO MENTAL PERFORMANCE CLASSIFICATION BASED ON EYE MOVEMENT MONITORING. // Сборник тезисов докладов конгресса молодых ученых. Электронное издание. – СПб: Университет ИТМО, [2024]. URL: https://kmu.itmo.ru/digests/article/12232