Eye Tracking Technology

As marketers try to understand more about user preferences, understanding the underlying emotions becomes more vital. Naturally, tracking real-time non-verbal cues, such as eye movement, can help brands realize their products' actual impact on the users.
Using sensors that track eye movement can help brands to detect the user presence and what they are looking at in real-time and gather immense information regarding user perception of the product. It considers several parameters such as pupil position, gaze point, and gaze vector of the eyes to help businesses map the user emotions towards the offerings. Consequently, marketers can design their marketing campaigns to be more attractive to the users and help them make a purchase decision sooner.

Eye tracking is a non-intrusive method of human behavioral research. However, eye-tracking uses multiple techniques to gather accurate insights, depending on the type of individuals it evaluates. Broadly, it follows three methods: attached, electric potential, and optical. The difference between these three is in the way the data is collected, which is:

• The attached technique collects data using a special device directly placed around the eye, such as a contact lens.
• The electric potential method uses electricity via electrodes placed around the eyes.
• Optical tracking uses reflected light and videos to determine eye movement.

Irrespective of the techniques used, eye tracking always tries to identify a few common aspects. It first determines the focus point and focal distance of the eyes and their direction. It also gathers information about eye movement during the head turn and tilt, the time spent on a particular point, and how fast they move during the process. Depending on the data collected, the tracking accuracy is processed.

Since eye tracking technology depends massively on the eyes' focus, the data interpretation is made by recording the eye position and movement. Depending on the technique used, near-infrared light detects the pupil center and identifies the detectable reflections in the pupil and cornea. It then calculates the vectors involved utilizing a method known as pupil center corneal reflection (PCCR) to understand the data. The efficiency of the process requires the infrared camera to be precise with the gaze direction measurement for proper demarcation of the pupil.
The pupil center and corneal reflection are closely related to the iris position. However, infrared lights allow a clear distinction between the iris and the pupil so as not to cause any distraction during the tacking process.

Several types of eye-tracking mechanisms are used depending on the requirements, specifications, and objectives of utilizing the technology. These are:

1. Head-Stabilized Eye Tracking:
   This type of system requires a method to restrict the participant's head movements, usually through a bite bar or chinrest. It is commonly used in high-fidelity research in neurophysiology or vision experiments where accuracy and precision precede participant comfort. Head stabilization may also be necessary with technologies like fMRI or MEG that immobilize the head.
   These systems are employed for three main reasons: to enhance accuracy and precision by eliminating head-movement artifacts and noise, provide a consistent visual experience for all participants, and complement other technologies requiring head stabilization. Head-stabilized eye tracking systems offer a level of precision that other systems cannot achieve. It uses a high-resolution camera that can take a closer image of the eye without needing to adjust for head movements. They can also achieve higher sample rates, allowing for faster eye movement analysis. These systems can be either monocular or binocular.
2. Remote eye-tracking:
   Remote eye-tracking systems don't require physical contact with the participant and instead use a camera positioned at a distance to track eye movements. The camera adjusts its view to account for head movements and uses pupil center and cornea reflection to track eye position and head orientation. Typically, the camera and IR source are positioned below the display, and the camera can be set in front of or attached to the screen or embedded in a device like a laptop or a kiosk. Remote systems have a working area called a "head box" and can only track eye movements within a defined "calibration plane," usually the computer screen. If the participant looks outside this area, tracking is temporarily disrupted, but an excellent remote system can quickly reacquire the eyes once they're back in range. Remote systems are commonly used for screen-based experiments or interactions and gaze-contingent interfaces like assistive technology or gaming laptops.
3. Mobile Eye-Tracking:
   Mobile eye tracking, also known as head-mounted eye tracking, involves a device worn by the participant, such as eye-tracking glasses or a headband. This system requires a camera or mirror to be positioned in the optical path of one or both eyes and an additional camera to record the scene or field of view. Gaze tracking in head-mounted systems is done with the entire field of view, making it useful for real-world experiments in sports, driving, social communication, mobile device testing, and more. The latest mobile systems are untethered, allowing for more realistic experiments during vehicle use, motor control, sports training, and store-shelf shopping. Head-mounted systems built into glasses are generally more comfortable, less invasive, and can be worn with other technologies like EEG.
   The use of mobile eye tracking enables studies in perception, communication, and other fields to be conducted in naturalistic and realistic contexts. In human factors and usability research, head-mounted eye tracking is often used to study interaction in industrial settings or when using real-world objects. For example, a car company can learn how changes to the design of a car's dashboard or sightlines can affect driver perception. An industrial engineer can study attention-based safety hazards in a factory or warehouse. In contrast, a usability engineer can check gaze during a wayfinding test for informational signs in an airport. Mobile eye-tracking systems are also employed to analyze the user experience of smartphone applications. Mobile eye-tracking systems are typically binocular, as tracking only one eye can result in parallax error, which affects the calculation of gaze data at depth due to the angle between the eyes and the scene camera.
4. Integrated or Embedded Systems:
   Eye-tracking devices can be integrated into various types of technology, including medical products, consumer electronics, and vehicle dashboards. In recent years, there has been an increase in the integration of eye-tracking devices into virtual and augmented reality devices for research and control purposes. One use of eye tracking in VR is foveated rendering. Higher-quality graphics are rendered at the point of gaze and lower quality in the periphery to save processing power. This requires fast sample rates and real-time data transmission. Eye tracking can also provide an intuitive control method for menus in AR and VR without a mouse or keyboard.

Although they might look similar, eye tracking and gaze tracking are quite different in nature and objective. Eye movement tracking is primarily used for research, and gaze tracking is more inclined toward communication technology. Depending on the movement patterns, and based on the purpose of tracking it, the equipment setup, identifying the measurement parameter, and drawing inference can differ.
Despite the difference, the eye tracker gathers insights from analyzing various gazing patterns. It can record information like gaze duration on a screen, head movements, and other details for analysis but is not used for communications. Rather, the primary purpose here is to collect information for research purposes, which can be used to treat various medical ailments like neurological issues.
Yet, this information can also help fine-tune the gaze technique parameters and derive intent-driven insights into customer preferences. Further, depending on other parameters like eye movement, realizing the impact of the communication the users are watching can be efficient.

Eye tracking technology is a valuable tool for studying cognitive processes such as visual attention, allowing researchers to quantify eye movements and determine where a participant's focus and visual field are attuned to while performing certain tasks. Visual attention is a complex cognitive phenomenon that includes three subtypes: spatial attention, feature-based attention, and object-based attention. Eye tracking software helps to quantify these movements for academic purposes across various fields, including linguistics research and developmental psychology.
Eye tracking provides numerical data about where the gaze is, including the coordinates in the x/y plane and confidence levels, which can be used to compute metrics like fixation and revisits. Eye tracking can capture everyday situations and processes that rely on visual attention, such as playing video games, reading, and buying behavior. Psychology and cognitive science experiments can be designed to study these contexts and analyze relationships between attention, performance, and eye movement. Eye-tracking technology can provide valuable insights into these attention-related functions across various psychological contexts across the target audience.

Eye tracking is challenging, even with wireless eye trackers and user-friendly software for researchers and marketers to gain deep insights into consumer behavior on websites, mobile sites, commercials, and product displays. However, the accuracy of eye-tracking data can still be questionable if researchers do not consider certain factors during the process, which may affect the final results.
Eye tracking is a technology that can quickly and easily analyze a person's viewing patterns to understand how they react to marketing tools. It allows researchers to intercept a person's gaze before they can control their eye movements and provides various metrics and statistics such as heatmaps, gaze plots, and fixation counts. However, even the most well-planned neuromarketing research may fail in real-life conditions. Testing the logic and equipment with a few participants is essential before launching a full-scale campaign analysis.
To ensure proper gaze mapping, it's crucial to calibrate the eye-tracking equipment correctly. It's also important to remember that participants may look beyond the testing object, so it's necessary to consider screen resolution and size. Heatmaps are a popular tool to analyze gaze patterns because they provide easy-to-understand visualizations of where users looked and which areas attracted their attention the most. However, supporting heatmaps with other eye-tracking metrics is recommended to identify outliers affecting data quality.
Central fixation bias is another common tendency for participants to look at the center of the image, which can lead to misleading results if the tested object is within this area. To mitigate this bias, it's best to analyze fixations of gaze that occur 1-2 seconds after the initial demonstration of the tested image and place the tested object outside the screen center. Additionally, researchers should avoid putting too many areas of interest on a page or tested thing, as eye trackers have a margin of error that can compromise gaze-catching accuracy.
Using fundamental eye-tracking tools, one can determine where, when, and what people are looking at and what they may miss. However, it is necessary to go beyond the basics to gain a deeper understanding of the subject's response.
One such method is to measure pupil size or dilation, which can provide insight into emotional engagement and cognitive workload. It is essential to note that pupil responses alone cannot indicate whether the emotional response is positive or negative.
Eye trackers can also measure the distance between the respondent and the screen and their relative position. It can provide information on approach-avoidance behavior, but interpreting the data is application-specific.
Ocular vergence, or the movement of the left and right eyes, can be measured independently, indicating whether the subject is focusing on something close or far away. Divergence, or when the eyes move apart, can indicate a loss of focus or concentration.
Finally, monitoring blinks can provide information on cognitive workload. A low frequency of blinks may indicate higher concentration levels, while a high frequency may indicate drowsiness and lower levels of focus.