Early Detection of Mental Health Using Eye Movement Data: A Cost-Effective Approach on Real Time Scenario

Publications

Early Detection of Mental Health Using Eye Movement Data: A Cost-Effective Approach on Real Time Scenario

Author : Dr Sahadeb Shit

Year : 2024

Publisher : Institute of Electrical and Electronics Engineers Inc.

Source Title : 2024 4th International Conference on Artificial Intelligence and Signal Processing, AISP 2024

Document Type :

Abstract

The human visual system, characterized by a complex array of eye movements, plays a pivotal role in our interaction with the environment. This paper explores the three fundamental types of eye movements – fixation, saccades, and smooth pursuit – and their significance in understanding mental health and cognitive functioning. Fixation reveals patterns linked to OCD and attention disorders, while saccadic activity reflects emotional states like anxiety and depression. Smooth pursuit indicates sustained attention, with disruptions highlighting cognitive impairments. Eye tracking technology, which precisely monitors these movements, provides insights into cognitive processes and emotional states, aiding mental health diagnostics. Web-based eye tracking, using personal computers and webcams, democratizes access to this technology, making it particularly beneficial for individuals, such as those with ASD, who faces challenges in verbal communication.