In this paper we investigate the utility of an eye-based interaction technique (EyeGrip) for seamless interaction with scrolling contents on eyewear computers. EyeGrip uses Optokinetic Nystagmus (OKN) eye movements to detect object of interest among a set of scrolling contents and automatically stops scrolling for the user. We empirically evaluated the usability of EyeGrip in two different applications for eyewear computers: 1) a menu scroll viewer and 2) a Facebook newsfeed reader. The results of our study showed that the EyeGrip technique performs as good as keyboard which has long been a well-known input device. Moreover, the accuracy of the EyeGrip method for menu item selection was higher while in the Facebook study participants found keyboard more accurate.
|ETRA '16 Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications
|Association for Computing Machinery
|8 mar. 2016
|Udgivet - 8 mar. 2016