DynamicRead: Exploring Robust Gaze Interaction Methods for Reading on Handheld Mobile Devices under Dynamic Conditions

Lei, Y., Wang, Y., Caslin, T., Wisowaty, A., Zhu, X., Khamis, M. and Ye, J. (2023) DynamicRead: Exploring Robust Gaze Interaction Methods for Reading on Handheld Mobile Devices under Dynamic Conditions. Proceedings of the ACM on Human-Computer Interaction, 7(ETRA), 158. (doi: 10.1145/3591127)

Abstract

Enabling gaze interaction in real-time on handheld mobile devices has attracted significant attention in recent years. An increasing number of research projects have focused on sophisticated appearance-based deep learning models to enhance the precision of gaze estimation on smartphones. This inspires important research questions, including how the gaze can be used in a real-time application, and what type of gaze interaction methods are preferable under dynamic conditions in terms of both user acceptance and delivering reliable performance. To address these questions, we design four types of gaze scrolling techniques: three explicit technique based on Gaze Gesture, Dwell time, and Pursuit; and one implicit technique based on reading speed to support touch-free, page-scrolling on a reading application. We conduct a 20-participant user study under both sitting and walking settings and our results reveal that Gaze Gesture and Dwell time-based interfaces are more robust while walking and Gaze Gesture has achieved consistently good scores on usability while not causing high cognitive workload.

• Item Type: Articles
• Keywords: Computer networks and communications, human-computer interaction, social sciences (miscellaneous).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Khamis, Dr Mohamed
• Authors: Lei, Y., Wang, Y., Caslin, T., Wisowaty, A., Zhu, X., Khamis, M., and Ye, J.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: Proceedings of the ACM on Human-Computer Interaction
• Publisher: Association for Computing Machinery (ACM)
• ISSN: 2573-0142
• ISSN (Online): 2573-0142
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in Proceedings of the ACM on Human-Computer Interaction 7(ETRA):158
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher