# Sensors, Techniques, and Future Trends of Human-Engagement-Enabled Applications: A Review
## 3 Sensors
### Eye Trackers  
Humans rely on their vision in most aspects of their lives. We obtain information about object features (such as size or colour) by looking at them, and we then integrate that information into how we interact with the world. We gather that information continuously by monitoring our environment or, in other terms, simply by looking around. Eye tracking technologies stem from the appeal of understanding human gaze in humans' perception-cognition-action processes. Gaze has long been regarded the most prominent nonverbal communicative signal [25]. Eye tracking helps to reveal a wealth of information to track and quantify human engagement [26]. There are different types of eye trackers, each based on distinct operating principles. In this section, we consider three kinds with a degree of mobility and thus real-world utility: head-mounted eye trackers, screen-based eye trackers, and integrated eye trackers. Head-mounted eye trackers, or eye tracking glasses, are worn by users allowing a range of free movement or unlimited movement [27]. Screen-based eye trackers usually do not have physical contact with users but require calibration to track eye movement on a screen [28]. Note that we exclude eye trackers that infer eye state from ambient cameras through AI. Those will be discussed in the next section. Finally, integrated eye trackers are built into other devices or technologies, such as Virtual Reality (VR) headsets. In clinical or research settings, we can moreover find eye tracking devices that involve attaching a special contact lens or head stabilization equipment, but we do not consider those due to the limitations in deployment. The eye trackers utilize visible or infrared light [27; 29] to infer the direction of human pupils and their projection in the world view, namely gazes and derived fixations. Modern devices offer additional cues, including saccade detection, blink detection, head pose estimation, Region-of-Interest (ROI) event tracking, pupil dilation, and integration of other sensing modalities to fully capture eye state and cues related to human attention. Capturing saccade and microsaccade cues requires a high sampling rate; e.g., high-end eye trackers with over 200 Hz sampling rate such as Tobii Pro series [30] are typically employed. Extra setups are usually needed to acquire head poses, e.g., by deploying QR codes in the environment [31] or using Inertial Measurement Units (IMUs) [32]. Screen-based eye trackers are further constrained in obtaining saccadic and head pose data. Aggregation of eye tracking data may present a rich set of behavioural characteristics, e.g., overlaying fixations to obtain heat maps and scanpath diagrams. The eye tracking cues yield many features that are directly associated with engagement, as shown in Table 1. Directed gaze refers to gaze landing on an object or group of objects led by an initiator implying immediate intention or interest [33]. Mutual gaze events, i.e., eye contact, have been extensively taken as a sign of bidirectional engagement intention [16; 33; 34]. [PERSON] et al. [35] investigated coordination of fixation and saccadic events in daily activities. The interplay between fixation and saccades usually reveal a strong indication of a subject's state of concentration as opposed to exploration or mind wandering. Blink frequency is one of the most far-reaching features in fatigue and drowsiness detection. First proposed in 1990s, PERCLOS [36] measures the percentage over time of eyelid closure over the pupil, reflecting droopy eye closure behaviours. [PERSON] et al. [37]utilized PERCLOS in conjunction with other eye events for driver fatigue monitoring. In the FatigueView dataset [38], PERCLOS realizes reliable performance despite being a generic and computationally inexpensive approach.