A Review of Pupillometry for Human-computer Interaction Studies

Abstract

The most commonly used methods in human-computer interaction (HCI) are based on behavioral data, interviews and questionnaires. While these practices are able to provide reliable results, they are influenced by subjective factors arising both from the experimenter’s and the user’s side. Many of these methods also have poor temporal resolution, limiting their range of use. Approaches based on physiological responses should not have these inherent shortcomings. Although there exist many methods based on different signals (EEG, ECG, EDA), pupillometry has its distinct advantages. The basic set of devices needed is cheap compared to most other methods and it is also the least intrusive option. It is well established that cognitive and affective processes can be monitored by recording changes in pupil dilation. While emotions are an important aspect of HCI and overall user experience, changes in mental effort levels are easier to interpret in case of software and webpage evaluation or interactions with automated systems. As a result, the present paper will focus on the measurement of mental effort, only mentioning other possible uses briefly. The goal of this review is to provide a brief insight on the issues that might arise during HCI studies and factors that should be controlled to gather valid data for mental effort calculations.