# Sensors, Techniques, and Future Trends of Human-Engagement-Enabled Applications: A Review
## 3 Sensors
### Eye Trackers
Pupil diameter (dilation) links biologically to the arousal system and norepinephrine neurons in the locus coeeruleus; pupil diameter is thus a useful independent measure of arousal and engagement that can be obtained from eye trackers beyond the eye position and gaze direction. The pupil diameter links to mind-wandering episodes [39]. Furthermore, the pupil diameter has been shown to be different in individuals with attention-deficit/hyperactivity disorder (ADHD) [40; 41], which is another indication that it links with attentional focus. Nonetheless, all mentioned types of eye trackers are cumbersome in practice. Subjects must wear bespoke glasses or directly face a designated screen. Screen-mounted eye trackers have a very confined effective range. Moreover, calibration per subject per trial is indispensable for most eye-tracking devices on the market. This severely constrains their \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Cues** & **Features** & & **Algorithm** \\ \hline \multirow{6}{*}{Gaze} & \multirow{6}{*}{\(\bullet\)} & \multirow{6}{*}{2D/3D Vector} & 1. & Image processing-based pupil tracking [42] \\  & & & 2. & Point-of-gaze (POG) estimation from pupil center and corneal reflection [43] \\  & & & 3. & Deep Learning methods, \\  & & & & e.g., [44] \\ \hline \multirow{6}{*}{Fixation} & \multirow{6}{*}{\(\bullet\)} & Total count \\  & & \(Min/max/total/mean/s.d.\) \\  & & (Standard Deviation) of duration \\  & & \(Min/max/total/mean/s.d.\) of \\  & & distance between \\  & & consecutive fixations \\ \hline \multirow{6}{*}{Saccade} & \multirow{6}{*}{\(\bullet\)} & Total count \\  & & \(Min/max/total/mean/s.d.\) \\  & & of duration \\  & & \(Min/max/total/mean/s.d.\) of \\  & & saccade amplitude \\ \hline \multirow{6}{*}{Blink} & \multirow{6}{*}{\(\bullet\)} & Total count \\  & & \(Min/max/total/mean/s.d.\) \\  & & of duration \\  & & Frequency (PERCLOS [36]) \\ \hline \multirow{6}{*}{ROI Events} & \multirow{6}{*}{\(\bullet\)} & Total entry/exit count \\  & & \(Min/max/total/mean/s.d.\) of \\  & & dwelling duration \\ \hline \multirow{6}{*}{Pupil Dilation} & \multirow{6}{*}{\(\bullet\)} & \multirow{6}{*}{\(Min/max/mean/s.d.\) of pupil dilation} & 1. & Shape-based pupil boundary detection [49] \\  & & & 2. & Edge detection and \\  & & & thresholding [50] \\ \hline \multirow{6}{*}{Head Pose 1} & \multirow{6}{*}{\(\bullet\)} & Pose \\  & & \(Min/max/mean/s.d.\) of \\ \cline{1-1}  & & angular velocity \\ \cline{1-1}  & & & \\ \end{tabular} \({}^{1}\) Algorithms are constrained in the scope of head pose detection with the aid of eye trackers.  
\end{table} 
Table 1: Features that can be extracted from eye-tracking cues and algorithms to derive them. usability. For instance, safety concerns and inconveniences could prevent usage in driving assistance, outdoor activities, and HRI. Because of these limitations, eye trackers are rarely used outside of controlled laboratory settings [15; 28; 35; 37; 52]. The eye movement pattern, modelling, and summaries of data findings are then distilled to formulate design choices; meanwhile, deploying eye trackers in real-world applications remains an expensive and obstructive option. Alternatively, eye state is acquired through other modalities in practice. One of the foremost options is the cameras which will be discussed in the following section.