Fuzzy Rule-Based Approach Towards Cognitive Load Measurement During Mental Task Using fNIRS

Every individual utilizes a different level of cognitive load for the same mental task. Measuring cognitive levels helps to design personalized instructional materials to enhance teaching-learning process and diagnose possible learning disabilities or neurodegenerative disorders. To acquire brain signals and measure the cognitive load, functional near infrared spectroscopy (fNIRS) is one of the popular non-invasive techniques. It is challenging to draw clear distinctions between the various cognitive states of the brain because of the complexity of the brain. A fuzzy system is designed where fuzzy inferencing rules and fuzzy membership functions are generated based on fuzzy c-means clustering. Three levels of cognitive load of the subjects as low, medium or high are considered based on the domain of the crisp output. The proposed fuzzy logic based model distinguishes the subjects based on their cognitive levels during mental tasks. We have worked on two available open-access fNIRS datasets. The outcomes shows the effectiveness of the proposed model.