Eye Tracking Analytics for Mental States Assessment - A Review

Fan Li, Gangyan Xu, Shanshan Feng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


Objectively measuring and monitoring human mental states in a non-intrusive way is important in improving the context-awareness of smart objects. One of the suitable bio-signals in measuring human mental states is aye-tracking data, as visual is the first channel of information collection. In addition, eye-tracking data shows the process of human-system interactions. Traditionally, many studies have been conducted to investigate the correlations between eye-tracking data and human mental states. Recently, with advanced artificial intelligence algorithms, the spatial and temporal patterns of eye-tracking data can be deeply analyzed for detecting human mental states. This study aims to explore and review eye-tracking parameters and state-of-art methods for mental states assessments. The study reveals that both statistical methods and novel methods, such as machine learning and deep learning have been applied to process eye-tracking data. Besides, novel features extracted from eye-tracking data, such as gaze-bin and entropy have been used in assessing human mental states. This review is expected to provide references for eye-tracking data analysis.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781665442077
Publication statusPublished - 6 Jan 2022
Event2021 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2021 - Melbourne, Australia
Duration: 17 Oct 202120 Oct 2021

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)1062-922X


Conference2021 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2021

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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