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Reading and Walking with Smart Glasses: Effects of Display and Control Modes on Safety.

Authors :
Huang, Yi-Jheng
Lin, Jing-Cheng
Lee, Suiang-Shyan
Wu, Bo-Jheng
Source :
International Journal of Human-Computer Interaction. Nov2023, p1-17. 17p. 13 Illustrations, 4 Charts.
Publication Year :
2023

Abstract

Abstract This paper intends to explore the safety of users using smart glasses to read articles while walking. We explore two factors of text presentation: the number of displayed words and the control methods of the text. Three text display modes (RSVP5, 3-lines, Page) and three text control modes (Auto, Manual, Mix) are designed and implemented. Two experiments were conducted to evaluate the effect of the text display and control methods. One is to evaluate the user’s responsiveness, assessing how quickly the user is allowed to initiate a behavior when faced with an immediate need to respond. The other is to evaluate the ability of users to observe the surrounding environment, assessing whether the user can have sufficient ability to notice when an abnormal situation occurs. Besides the safety aspects, we also measure users’ cognitive workload, system usability, and other subjective statistics as their user experience. The experimental results showed that in the display modes, providing too much text at one time reduced the user’s ability to respond, and the RSVP5 display mode resulted in a poorer user experience. In terms of the control modes, the mix control modes make it easier for users to ignore their surroundings, and the auto control mode gets the worst user experience. As a result, when considering both safety and user experience, we suggest a smart glasses reading system should display a few lines of text at a time and let the users fully and manually control the text. Finally, a few guidelines are provided suggesting how to design a smart glasses reading system for pedestrians. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10447318
Database :
Academic Search Index
Journal :
International Journal of Human-Computer Interaction
Publication Type :
Academic Journal
Accession number :
173465641
Full Text :
https://doi.org/10.1080/10447318.2023.2276529