Study of smart watch interface usability evaluation based on eye-tracking

Abstract

Nowadays the intelligence of watches brings users brand new experience, and at the same time it makes human-watch interaction relationship becomes more and more complicated, therefore the design of smart watch interface faces greater challenge. As the interface of smart watches delivers more and more information, how to guarantee favorable usability of smart watch interface becomes the focus of designers. Designers need more objectively evaluate the reasonableness of smart watch interface layout and the visibility of interface elements. But traditional evaluation indexes can’t intuitively reflect whether the system structure conforms to the thinking mode of users; and traditional evaluation indexes can’t reveal the strategies employed on interface by users. In this study smart watch interface user performance test is carried out and eye movement tracking technology is introduced into usability evaluation of smart watch interface to measure the usability level of smart watch interface and quantity analysis on internal differences among smart watch interfaces is conducted. It is founded from task test result that eye movement data can well compare internal differences among watch interfaces and reveal how users search their target options and information on smart watch interface. Compared with the previous studies, in this study the author proposes smart watch usability evaluation method based on eye movement, applies eye movement data in usability evaluation index system to reveal users’ thinking for the designer and provide the clue of solving usability problems. These results have great significance in guiding the practice of smart watch usability evaluation and further perfecting usability evaluation index system. Eye movement tracking technology is used in this study so that it can comprehensively and objectively evaluate usability level of smart watch interface and provide objective evidence for designer to improve the interface of smart watch and improve the usability level. The following results are obtained from the study: 1 Eye movement data such as fixation time and fixation point number are used as quantified indexes to evaluate interface information structure and interface element representation meaning. And the eye movement data can effectively evaluate the internal differences of watch interfaces and measure usability level of watch interfaces. 2 Fixation time hot spot diagram obtained from graphic eye movement data can intuitively reflect the attention layout of tested users on interface and provide objective evidences for experimenter to analyze interface problems. 3 Eye movement video can reappear the activity of sight line when tested users use the smart watch interface. Many interface problems at deep levels can be found using the analysis method of combining eye movement video and graphic eye movement data. 4 Interface usability evaluation method based on eye movement tracking applies in early and middle stage of smart watch design and provide objective evidences for designers to understand users’ thinking and improve interface design.