Where do we look? What do we look at, and how much time do we spend looking at it? How do our pupils react to different kinds of visual stimulation? When exactly do we blink?

Put simply, eye tracking refers to the measurement of eye activity. More specifically, eye tracking describes the recording of eye position and movement in an environment based on the optical tracking of corneal reflections to assess visual attention. While the idea of eye tracking is quite straightforward, the technology behind it might strike you as rather complex and inaccessible.

No need to hit the panic button. This page is packed with all the need-to-knows and useful tools to help you get a solid grasp of eye tracking technology and best practices.

The technology behind eye tracking

– How exactly does eye tracking work?

Eye tracking use is on the rise. While early devices were highly intrusive and involved particularly cumbersome procedures to set up, modern eye trackers have undergone quite a technological evolution in recent years. Long gone are the rigid experimental setups and seating arrangements you might think of.

Modern eye trackers are hardly any larger than smart phones and provide an extremely natural experience for respondents.

Remote, non-intrusive methods have made eye tracking both an easy-to-use and accessible tool in human behavior research that allows objective measurements of eye movements in real-time.

The Technology

Most modern eye trackers utilize near-infrared technology along with a high-resolution camera (or other optical sensor) to track gaze direction. The underlying concept, commonly referred to as Pupil Center Corneal Reflection (PCCR), is actually rather simple.

It essentially involves the camera tracking the pupil center, and where light reflects from the cornea. An image of how this looks like is on the right. The math behind it is …well, a bit more complex. We won‘t bore you with the nature of algorithms at this point.

Image above: Pupil Center Corneal Reflection (PCCR). The light reflecting from the cornea and the center of the pupil are used to inform the eye tracker about the movement and direction of the eye.

Why infrared spectrum imaging?

The accuracy of eye movement measurement heavily relies on a clear demarcation of the pupil and detection of corneal reflection.

The visible spectrum is likely to generate uncontrolled reflections, while illuminating the eye with infrared light – which is not perceivable by the human eye – renders the demarcation of the pupil and the iris an easy task – while the light directly enters the pupil, it just reflects from the iris.

This means that a clear contrast is generated (with little noise) and can, therefore be followed by algorithms (running inside the eye tracker) with ease.

Here‘s the bottom line of how it works:

Near-infrared light is directed toward the center of the eyes (the pupils) causing visible reflections in the cornea (the outer-most optical element of the eye), and this high-contrast image is tracked by a camera.

Eye tracking devices

There are three main types of eye tracker:

Screen-based (also called remote or desktop) glasses, (also called mobile) and eye tracking within VR headsets. Webcam-based eye tracking has been seen as an option, but this technology is inherently inferior to infrared-based eye trackers (something we cover in this blog post).

Gaze data accuracy

– How do the trackers compare?

Measurement precision certainly is crucial in eye movement research. The quality of the collected data depends primarily on the tracking accuracy of the device you use. Going for a low quality system will prevent you from being able to extract high precision data.

A common misconception is that researchers face an inevitable trade-off between measurement accuracy and the amount of movement the respondent can make with their head. The truth is a bit more complex than that

Screen-based eye trackers:

Require respondents to sit in front of a screen or close to the stimulus being used in the experiment. Although screen-based systems track the eyes only within certain limits, they are able to move a limited amount, as long as it is within the limits of the eye tracker’s range. This range is called the headbox. The freedom of movement is (usually) sufficiently large for respondents to feel unrestricted.

Eye tracking glasses:

Are fitted near the eyes and therefore allow respondents to move around as freely as they would like – certainly a plus if your study design requires respondents to be present in various areas (e.g. a large lab setting, or a supermarket).

Does that imply that eye tracking glasses are more susceptible to measurement inaccuracies?

Not at all. As long as the device is calibrated properly, head-mounted eye trackers are unaffected by head movements and deliver high precision gaze data just like screen-based devices. Also, as the eye tracking camera is locked to the head‘s coordinate system, the overlaying of eye movements onto the scene camera does not suffer from inaccuracies due to head movement. Who uses eye tracking? – Use cases in research You may be surprised to discover that eye tracking is not exactly a novelty – it has in fact been around for many years in psychological research. Given the well-established relationship between eye movements and human cognition, it makes intuitive sense to utilize eye tracking as an experimental method to gain insight into the workings of the mind.

If eye tracking is old news, how come it is the latest buzz in human behavior research?

First let‘s rewind a bit. Studies of eye movements based on simple observation stretch back more than 100 years ago. In 1901, the first eye tracker was built, but could only record horizontal eye movements and required a head-mount. In 1905, eye movements could be recorded using “a small white speck of material inserted into the participant‘s eyes“. Not exactly the most enjoyable experimental setup. It‘s safe to say that eye tracking has come a long way. With technological advancements, modern eye trackers have became less intrusive, more affordable, accessible, and experimental sessions have became increasingly comfortable and easier to set up (long gone are the scary “white specks“ and head-mounts). Currently, eye tracking is being employed by psychologists, neuroscientists, human factor engineers, marketers, designers, architects – you name it, it’s happening. In the following pages, we’ll go through some of the most common application areas for eye tracking, and see how it helps guide new discoveries and insight in each. 1. Neuroscience & psychology thrive on eye tracking Neuroscience and psychology utilize eye tracking to analyze the sequence of gaze patterns to gain deeper insights into cognitive processes underlying attention, learning, and memory. How do expectations shape the way we see the world? For example, if you see a picture of a living room, you will have an idea of how the furniture should be arranged. If the scene doesn’t match your expectations, you might be baffled and gaze around the scene as your “scene semantics” (your “rules” of how a living room should look) are violated. Another research area addresses how we encode and recall faces – where do we look to extract the emotional state of others? Eyes and mouth are the most important cues, but there’s definitely a lot more to it. Another research area addresses how we encode and recall faces – where do we look to extract the emotional state of others? Eyes and mouth are the most important cues, but there’s definitely a lot more to it. Eye tracking can also provide insights into processing of text, particularly how eye movements during reading are affected by the emotional content of the texts. Eye tracking can provide crucial information about how we attend to the world – what we see and how we see it. 2. Eye tracking delivers unmatched value to market research Why is it that some products make an impression on customers while others just don‘t get it right? Eye tracking has become a popular, increasingly vital tool in market research. Many leading brands actively utilize eye tracking to assess customer attention to key messages and advertising as well as to evaluate product performance, product and package design, and overall customer experience. When applied to in-store testing, eye tracking provides information about the ease and difficulty of in-store navigation, search behavior, and purchase choices. 3. Simulation There are various different ways in which to investigate human behavior in simulations. One of the most common approaches is to use a driving simulator. Such research often use eye tracking glasses combined with a several other sensors to gain a better understanding of human behavior in hazardous situations. Where do drivers look when they face obstacles on the street? How does talking on the phone affect driving behavior? How exactly does speeding compromise visual attention? Insights of that kind can help improve hazard awareness and be applied to increase future driver safety. Automotive research has embraced eye tracking glasses for a long time to asses the drivers‘ visual attention – both with respect to navigation and dashboard layout. In the near future automobiles might even be able to respond to the drivers’ eye gaze, eye movements, or pupil dilation.

4. Eye tracking can help gain deep insights with Human Computer Interaction (HCI) So what is Human Computer Interaction (HCI)? Essentially, HCI research is concerned with how computers are used and designed, and how this relates to their use by people. From laptops, tablets, smart phones, and beyond, he use of technology can be evaluated by measuring our visual attention to the devices we use. 5. Website testing A rapidly growing field that utilizes eye tracking as a methodology for assessment is usability and user experience testing. Eye tracking for website testing is an often utilized approach, giving insights into how websites are viewed and experienced. How do people attend to adverts, communication, and calls to action (CTAs)? If you‘re losing out on revenue, eye tracking data can deliver valuable insights into the gaze patterns of your website visitors – how long does it take them to find a specific product on your site, what kind of visual information do they ignore (but are supposed to see)? Cut to the chase and see exactly what goes wrong. The very same investigations can even be applied to mobile apps on tablets and smartphones.

6. Learning & education can benefit from eye tracking

What if learning could be an equally satisfying experience for all of us? What exactly does it take to make learning a success? In recent years, eye tracking technology has impressively made its way into educational science to help gain insights into learning behavior in diverse settings ranging from traditional “chalk and talk“ teaching approaches to digital learning.

Analyzing visual attention of students during classroom education, for example, delivers valuable information in regard to which elements catch and hold interest, and which are distracting or go unseen.

Do students read or do they scan slides? Do they focus on the teacher or concentrate on their notes? Does their gaze move around in the classroom? Eye tracking findings like these can be effectively used to enhance instructional design and materials for an improved learning experience in the classroom and beyond.

7. Eye tracking is used in medical research to study a wide variety of neurological and psychiatric conditions

Eye tracking in combination with conventional research methods or other biosensors can help assess and potentially diagnose conditions such as Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), Obsessive Compulsive Disorder (OCD), schizophrenia, Parkinson‘s disease, and Alzheimer‘s disease.

Additionally, eye tracking technology can be used to detect states of drowsiness or support multiple other fields of medical use, quality assurance or monitoring.

8. Gaming and UX – why is eye tracking the big hit among web designers and developers?

Eye tracking has recently been introduced into the gaming industry and has since become an increasingly prominent tool as Designers are now able to assess and quantify measures such as visual attention and reactions to key moments during game play to improve the overall gaming experience.

When combined with other biometric sensors, designers can utilize the data to measure emotional and cognitive responses to gaming. New trends and developments may soon render it possible to control the game based on pupil dilation and eye movements.

Eye tracking data

– Understanding the results

Eye tracking makes it possible to quantify visual attention like no other metric, as it objectively monitors where, when, and what people look at.

Eye tracking metrics

Fixation and Gaze points

Without a doubt, the terms fixation and gaze points are the most prominent metrics in eye tracking literature.

Gaze points constitute the basic unit of measure – one gaze point equals one raw sample captured by the eye tracker. The math is easy: If the eye tracker measures 60 times a second, then each gaze point represents a sixtieth of a second (or 16.67 milliseconds).

If a series of gaze points happens to be close in time and range, the resulting gaze cluster denotes a fixation, a period in which our eyes are locked toward a specific object. Typically, the fixation duration is 100 – 300 milliseconds.

The eye movements between fixations are known as saccades. What are they exactly? Take reading a book, for example. While reading, your eyes don’t move smoothly across the line, even if you experience it like that. Instead, your eyes jump and pause, thereby generating a vast number of discrete sequences. These sequences are called saccades.

Perceptual span and smooth pursuit

Reading involves both saccades and fixations, with each fixation involving a perceptual span. This refers to the number of characters we can recognize on each fixation, between each saccade. This is usually 17-19 letters, dependent on the text. Experienced readers have a higher perceptual span compared to early readers, and can therefore read faster.

Imagine watching clouds in the sky as you pass your time waiting at the bus stop. As you now know about saccades, you might expect your eye movements to in this scenario to behave in the same way – but the rules are a bit different for moving objects. Unlike reading, locking your eyes toward a moving object won’t generate any saccades, but a smooth pursuit trajectory. This way of seeing operates as you might expect – the eyes smoothly track the object. This occurs up to 30°/s – at speeds beyond this, saccades are used to catch up to the object.

As fixations and saccades are excellent measures of visual attention and interest, they are most commonly used to fuel discoveries with eye tracking data.

Now let‘s get practical and have a look at the most common metrics used in eye tracking research (that are based on fixations and gaze points) and what you can make of them.

Heat maps

Heat maps are static or dynamic aggregations of gaze points and fixations revealing the distribution of visual attention.Following an easy-to-read color-coded scheme, heat maps serve as an excellent method to visualize which elements of the stimulus were able to draw attention – with red areas suggesting a high number of gaze points (and therefore an increased level of interest), and yellow and green areas showing fewer gaze points (and therefore a less engaged visual system. Areas without coloring were likely not attended to at all.

Areas of Interest (AOI) Areas of Interest, also referred to as AOIs, are user-defined subregions of a displayed stimulus. Extracting metrics for separate AOIs might come in handy when evaluating the performance of two or more specific areas in the same video, picture, website or program interface. This can be performed to compare groups of participants, conditions, or different features within the same scene Fixation sequences Based on fixation position (where?) and timing information (when?) you can generate a fixation sequence. This is dependent on where respondents look and how much time they spend, and provides insight into the order of attention, telling you where respondents looked first, second, third etc. This is a commonly used metric in eye tracking research as it reflects salient elements (elements that stand out in terms of brightness, hue, saturation etc.) in the display or environment that are likely to catch attention.