Using Eye Tracking to Aid the Design of Human–Machine Interfaces (HMIs) in Industrial Applications

Abstract In the vision of a “hybrid society,” the interaction between humans and embodied digital technologies is envisaged to be as smooth and seamless as human–human interaction. In the foreseeable future, however, humans will undoubtedly continue to interact with many machines through designated human–machine interfaces (HMIs). Designing such HMIs for production settings presents a particular challenge, as users may vary in their experience and expertise. Moreover, challenging issues of a specific HMI are often difficult to verbalize and therefore hard to obtain through user report and expert interviews alone. To make interactions through HMIs smooth, it is therefore crucial to evaluate HMIs with state-of-the-art technologies that do not require explicit report. Here, we demonstrate the use of eye tracking for HMI design in an industrial production setting, where smooth human–machine interaction is particularly critical to ensure safe and efficient operation. Using a real-life example, we illustrate how eye tracking allows dissociating users’ difficulties to find a particular interaction item (“search”) from their challenges in realizing that it is indeed the item to be operated (“verification”). We argue that this distinction is crucial for (re-) designing HMIs to optimize usability and that the usefulness of eye tracking extends beyond the specific context to human–machine interaction in general.