Measuring dwell time percentage from head-mounted eye-tracking data – comparison of a frame-by-frame and a fixation-by-fixation analysis

Abstract

Although analysing software for eye-tracking data has significantly improved in the past decades, the analysis of gaze behaviour recorded with head-mounted devices is still challenging and time-consuming. Therefore, new methods have to be tested to reduce the analysis workload while maintaining accuracy and reliability. In this article, dwell time percentages to six areas of interest (AOIs), of six participants cycling on four different roads, were analysed both frame-by-frame and in a 'fixation-by-fixation' manner. The fixation-based method is similar to the classic frame-by-frame method but instead of assigning frames, fixations are assigned to one of the AOIs. Although some considerable differences were found between the two methods, a Pearson correlation of 0.930 points out a good validity of the fixation-by-fixation method. For the analysis of gaze behaviour over an extended period of time, the fixation-based approach is a valuable and time-saving alternative for the classic frame-by-frame analysis.

Visual Eye Gaze While Cycling: Analyzing Eye Tracking at Signalized Intersections in Urban Conditions

“…In this respect, "dwell-time fixation" is defined by a minimum fixation duration of 100 ms and a maximum visual angle variation of one degree. Consistent with protocol from similar studies [36,[42][43][44], if the visual angle varies up to one degree, it means that the gaze is fixed; the end of a fixation is defined when the eye deviates from the fixation start position by more than one degree. The list of variables measured in this study are presented in Table 1 with their description; Table 2 presents how the analysis is segmented by type of intersection and experience level.…”

Evaluation of eye, head and trunk coordination during target tracking tasks

“…This procedure was time consuming and should be automated in the future. According to Vansteenkiste and colleagues (Vansteenkiste et al, 2015), head-mounted eye-tracking data are still very time-consuming and data processing is a major drawback. Finally, additional subjects are needed to establish normative data that would be generalizable.…”

“…There is limitation in the literature concerning the accuracy of target fixation and coordination of eye and head movement to achieve fixation including response time and velocity, and analysis of gaze is still a challenge. More standardized procedures for head-mounted gaze analysis is needed (Vansteenkiste et al, 2015). This is important because it provides information on strategies used by eye and head to achieve a stable movement and gaze control.…”

A study on eye fixation patterns of students in higher education using an online learning system

“…Another study also highlights that learners' cognitive load fluctuates during interaction while using online learning tools [4]. From prior research studies, cognitive activities and deep thinking has corresponded to measurements such as eye fixations, saccades, dwell time percentage, pupil diameter and blink rate [4,24,27,28,29]. It is unclear, however, as to how these measurements eye movements by learners are related to their learning experiences, and if learning indeed do occurs, how such readings are related to individual academic results in recent past, or use as a predictive method for future academic performances.…”