Pupil Labs Blog

Research is unique and needs unique solutions. Experiments vary enormously. A good eye tracking system should be able to adapt to different participants, sensors, environments, and experimental setups.

Why gaze alone is not always enough, and why data rate matters. Gaze is only one output of an eye tracker. The underlying measurements, their sampling rates, and access to additional sensor data can determine what questions you are able to answer.

Reliable measurements as wearers, device fit, movement, lighting, and environments vary. Robustness determines whether an eye tracker can maintain measurement availability and performance as the conditions around it change.

Removing calibration changes more than the setup procedure. It can reduce interruptions, simplify integration, and extend eye tracking to some participants who find conventional calibration difficult.

What does it mean, how is it measured, and how much do you actually need? Accuracy is one of the most commonly compared eye tracking specifications, but the number alone rarely tells the whole story.

What Makes a Good Eye Tracker? A Guide for Research and Industry