Document Type

Conference Paper

Publication Date

2023

DOI

10.1145/3588015.3589537

Publication Title

ETRA '23: Proceedings of the 2023 Symposium on Eye Tracking Research and Applications

Pages

27 (1-3)

Conference Name

ETRA '23: 2023 Symposium on Eye Tracking Research and Applications, May 30-June 2, 2023, Tubingen, Germany

Abstract

Eye tracking measures can provide means to understand the underlying development of human working memory. In this study, we propose to develop machine learning algorithms to find an objective relationship between human eye movements via oculomotor plant and their working memory capacity, which determines subjective cognitive load. Here we evaluate oculomotor plant features extracted from saccadic eye movements, traditional positional gaze metrics, and advanced eye metrics such as ambient/focal coefficient , gaze transition entropy, low/high index of pupillary activity (LHIPA), and real-time index of pupillary activity (RIPA). This paper outlines the proposed approach of evaluating eye movements for obtaining an objective measure of the working memory capacity and a study to investigate how working memory capacity is affected when reading AI-generated fake news.

Original Publication Citation

Abeysinghe, Y. (2023). Evaluating human eye features for objective measure of working memory capacity. In E. Kasneci, F. Shic, M. Khamis (Eds.), ETRA '23: Proceedings of the 2023 Symposium on Eye Tracking Research and Applications (27). Association for Computing Machinery. https://doi.org/10.1145/3588015.3589537

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