Abstract
Technology to monitor mental health is gaining popularity as it helps to improve the cognitive and behavioral performance of an individual. Considering the growing need to monitor mental health, there is subsequent research in continuous and real-time monitoring technologies that can increase the quality of life by reducing the cost of health care. Eye tracking technology has played a significant role in monitoring a person's mental health. An intelligent system can apply several computational procedures to extract meaningful information from the massive physiological data obtained from eye tracking. The proposed model IntelEye is a tool to detect the stressful states of an individual while watching calm and stressful videos. The eye gaze measures based on pupil diameter, fixation, and blink were used for detecting stressful conditions. The data was collected from hospital employees, and the K Nearest Neighbor algorithm could successfully recognize the stressful states and the corresponding gaze location during stressful situations. IntelEye is not only identifying the stressful states but also has the novelty of identifying the scene and gaze location, making them stressful while watching the video.
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