ABSTRACT
The growing number of people with cognitive impairment will significantly increase healthcare demand. Screening tools are crucial for detecting cognitive impairment due to a shortage of mental health experts aiming to improve the quality of life for those living with this condition. Eye tracking is a powerful tool that can provide deeper insights into human behavior and inner cognitive processes. The proposed Eye-Tracking-Based Trail-Making Test, ETMT, is a screening tool for monitoring a person's cognitive function. The proposed system utilizes a fuzzy-inference system as an integral part of its framework to calculate comprehensive scores assessing visual search speed and focused attention. By employing an adaptive neuro-fuzzy-inference system, the tool provides an overall cognitive-impairment score, allowing psychologists to assess and quantify the extent of cognitive decline or impairment in their patients. The ETMT model offers a comprehensive understanding of cognitive abilities and identifies potential deficits in various domains. The results indicate that the ETMT model is a potential tool for evaluating cognitive impairment and can capture significant changes in eye movement behavior associated with cognitive impairment. It provides a convenient and affordable diagnosis, prioritizing healthcare resources for severe conditions while enhancing feedback to practitioners.
Subject(s)
Cognitive Dysfunction , Eye-Tracking Technology , Humans , Quality of Life , Neuropsychological Tests , Cognitive Dysfunction/diagnosis , CognitionABSTRACT
In the current education environment, learning takes place outside the physical classroom, and tutors need to determine whether learners are absorbing the content delivered to them. Online assessment has become a viable option for tutors to establish the achievement of course learning outcomes by learners. It provides real-time progress and immediate results; however, it has challenges in quantifying learner aspects like wavering behavior, confidence level, knowledge acquired, quickness in completing the task, task engagement, inattentional blindness to critical information, etc. An intelligent eye gaze-based assessment system called IEyeGASE is developed to measure insights into these behavioral aspects of learners. The system can be integrated into the existing online assessment system and help tutors re-calibrate learning goals and provide necessary corrective actions.
