The purpose of this study is to dissociate pupillary changes due to cognition from pupillary response to light. There is scientific evidence suggesting that the pupil dilates systematically in response to cognitive effort. However, the pupil is also systematically affected by the level of brightness of the surrounding. Our study induces controlled levels of brightness, along with controlled levels of cognition, for identifying pupillary markers specific to cognitive activity only. The data recorded was processed through a three-way ANOVA (control x brightness x cognition) to ensure the reliability of our indices, and a support vector machine algorithm was used to classify the different conditions.
Niamba, Kouadio M., "A Support Vector Machine Application for the Detection of Pupillary Markers of Cognitive Workload" (2021). IdeaFest. 399.