Last year, FMG’s user experience (UX) team presented “Exploring the Relationship Between Eye Movements and Pupillary Response from Formative User Experience Research” at the Human-Computer Interaction International Conference. The study examined the relationship between pupil diameter and fixations in the context of a usability task. Specifically, our team used UX-generated data to explore whether fixation measures and pupil diameter measures correlate, and under which conditions this relationship occurs for this type of study.
The measurement of changes in pupil diameter due to presentation of different stimuli is called pupillometry. This is a continuous variable recorded at every observation captured by the eye tracker and, as eye-tracking equipment continues to evolve and improve, pupillometry continues to be captured more accurately and at a higher sampling rate. Improvements in eye tracking hardware and software now allow analyses to be conducted that were once impractical for UX researchers. Very slight but measurable changes in pupil diameter have been attributed to differing levels of mental workload, cognitive processing, attentional effort, perception, memory load, decision making, and physiological arousal.
A key finding from the study was that the longer a person fixates on a website, the smaller his or her pupil diameter becomes for that fixation. The study also found that participants who fixate for longer durations have less consistency in their pupil size than those who fixate for shorter durations. These findings, along with others, demonstrate that even for usability tasks with low complexity, there can still be significant variations in pupil diameter (and, by implication, cognitive workload) and that these variations in pupil diameter can demonstrate consistent relationships with fixation count and length.
Gaze patterns, measured by fixation counts and fixation durations, can be used to assess visual attention and the level of cognitive processing required to process a certain stimulus. Although self-reported metrics (e.g., System Usability Scale (SUS) questionnaire, satisfaction questionnaire, NASA Task-Load Index) and performance metrics (task success/fail) are the two most commonly used measures of user experience, physiological metrics (e.g., eye movements and pupillary response) can provide additional insights. These physiological measurements can provide more detailed insight into the mental workload of users as they interact, for example, with an interface rather than traditional subjective measures like the NASA Task-Load Index. People might self-report experiencing a low mental workload even though their gaze patterns and pupillometry data suggest they are experiencing difficulty locating or processing information.
Ultimately, the goal of this line of research is to further the understanding of pupillometry in usability testing contexts. Building on this body of knowledge will help teams understand the benefits and limitations of incorporating pupillometry in usability tests as well as how to interpret results. Gaining access to such accurate and consistent pupillometry data opens up exciting possibilities!