A note on eye tracking and its research applications

How your eyes betray your thoughts…

Writer: Chrysi Anastasaki
Editor: Eleanor Mackle
Artist: Rosie Jarett

The concept of studying eye movements has been around since the 1800s, when psychologists observed ‒ without advanced technology ‒ how the eyes change position while reading a script or staring at a photo. Today, eye tracking can be used to reveal what people engage with, and what they ignore, during activities that require visual attention. On a daily basis, we spend little time thinking about the position of our eyes, or how many times we blink, but our eye moments can actually give hints about our thoughts to the people who know how to look for them.

The eye is the organ of vision, which responds to the stimulus of light. Eye-tracking technology measures a person’s eye movements: where they look, what they see (or do not see), and for how long they gaze at one spot. These eye movements are categorised as either ‘saccades’ (when the eyes jump quickly from one object to another), ‘fixations’ (when the eyes stop to rest on an object) or ‘smooth pursuit’ (when the eyes follow a moving object). By analysing these motions, researchers can gain information about our hidden cognitive processes. 

Eye trackers are devices that use a combination of sensory technologies and high-definition cameras to follow and record eye movements. Near-infrared light is projected onto the eye and reflects off the clear outer layer (the cornea). The direction of the reflected light is noted and used by advanced algorithms to calculate the exact position of the eye. This occurs many times per second, so that movements can be captured with high precision. There are various types of eye trackers ‒ screen-based, wearable, webcam ‒ making them versatile tools that can be used in most instances where mental processes are being investigated. 

The benefits of eye-tracking technology include the fact that it is safe, affordable, and portable. Furthermore, tests can be carried out on both healthy volunteers and patients, which is not always the case with brain imaging modalities such as functional magnetic resonance imaging (fMRI). On the other hand, it is still a technique that requires laboratory conditions to conduct experiments. This can prohibit observation of the natural behaviour of participants, who might behave differently in a lab setting to the way they would in real life. Another key consideration when using eye tracking is that it cannot explain the reasons behind observations. Therefore, it is worth combining eye tracking with other quantitative and qualitative techniques to maximise its potential for robust and accurate results.

Psychology, neuroscience and other disciplines have endorsed eye tracking in their research. One of the most relevant topics is pupillometry, which measures changes in the pupil diameter. The study of pupil dilation has been connected to factors such as drug use or to cognitive features such as intelligence.  

Developmental disorders, such as autism, have been studied with eye tracking ‒ particularly as reduced eye contact is a hallmark of autism. According to a study from 2007, autistic people spend less time looking at the core features of a face such as the nose, mouth and eyes, compared with non-autistic people. This type of study can reveal information about the way autistic people process the world around them, and lead to a better understanding of the disorder.  

Another interesting use of eye tracking is in examining human perception of qualities such as beauty. One study measured the perceived beauty of the Great Barrier Reef by asking people to observe pictures of turtles, coral, sand, sea and water contamination and rate their beauty. Eye movements, such as fixations, indicated that subjects spent more time on a beautiful picture, compared to an ugly one. This is useful in a broad range of applications, from social psychology to advertising and marketing. 

Recently, eye tracking has been used to examine how people ingest actual news, as opposed to fake news. A team of researchers altered news articles by adding false words into the original headlines. The study participants were found to spend less time looking at the fake headlines compared to the real articles. The results were then used to build an algorithm to predict whether a news headline was fake or not, based on an observer’s eye movements. This suggests that in the future, machine learning could be combined with eye tracking to enhance its capabilities, and even to tackle misinformation.  

It is clear that eye tracking is a useful tool, with a relatively simple principle: the movement of the eyes can be an indicator of thought and behaviour. So far, this has been used in a wide range of applications ‒ from probing beauty perception and autism to building fact-checking tools. Technological innovation is enhancing eye-tracking capabilities at an astounding rate; it may not be long before its achievements make you doubt your own eyes.

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