## 3 Dataset Description
### OperatorYEVP Dataset  
For this purpose, we utilized the OperatorYEVP dataset as introduced by [13]. This dataset features video recordings of ten unique individuals participating in diverse activities. These activities were documented at three distinct moments throughout the day (morning at 9:00 a.m., afternoon at 13:00 p.m., and evening at 18:00 p.m.), over a period spanning eight to ten days. The recordings occurred on weekdays from December 2022 to June 2023. The recorded data not only offer a frontal view of the participants' facial expressions, but they also include a set of additional information. This encompasses data pertaining to pupil and head movement (including specific coordinates), scene visuals, pulse rate for each interval, and Choice Reaction Time measured twice. Furthermore, the dataset incorporates responses to various questionnaires and scales, notably the VAS-F scale. The VAS-F scale, an 18-question measure, addresses the subjective experiences of fatigue among participants. It is worth noting that these questions were administered prior to the beginning of the experimental session. The timeline of a session is shown in Figure 1. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Dataset** & \begin{tabular}{c} **Number of** \\ **Subjects** \\ \end{tabular} & **Age Range** & **Number of Videos** & **Illumination** & **Camera Type** & **Human State** \\ \hline UTA-RLDD [32] & 60 & 20–59 & 180 & Daytime and nighttime & RGB & \begin{tabular}{c} Alertness, \\ low vigilance, and \\ drowness \\ \end{tabular} \\ \hline YawDD [23] & 107 & - & 322 and 29 & Daytime & RGB & \begin{tabular}{c} Talking, \\ yawning, and \\ laughing \\ \end{tabular} \\ \hline [PERSON] et al. [22] & 10 & - & 20 & Daytime & RGB & \begin{tabular}{c} Talking, \\ yawning, and \\ laughing \\ \end{tabular} \\ \hline NTHU-DDD [33] & 36 & - & 360 & Daytime and nighttime & RGB and IR & \begin{tabular}{c} Nodding, \\ regular driving, \\ yawning, \\ slow blinking, and \\ laughing \\ \end{tabular} \\ \hline Licensed & 5 & 30–50 & - & Daytime & RGB & \begin{tabular}{c} Alertness, \\ low vigilance, and \\ fatigue \\ \end{tabular} \\ \hline DROZY [35] & 14 & \(22.7\pm 2.3\) & - & \begin{tabular}{c} 1 st PVT: 8:30 a.m. \\ 2 nd PVT: 3:30 a.m. \\ 3 rd PVT: 12:00 p.m. \\ \end{tabular} & IR & \begin{tabular}{c} Alertness, \\ low vigilance, and \\ drowsiness \\ \end{tabular} \\ \hline FatigueView [37] & 95 & Over 18 & 124 million frames & Daytime and nighttime & RGB and IR & \
\begin{tabular}{c} Normal, \\ alertness, \\ signs of sleepness, \\ sleepness \\ \end{tabular} \\ \hline SUST-DDD [38] & 19 & 24–42 & 2074 & Reduced daylight & RGB &
\begin{tabular}{c} Normal and \\ drowsiness \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary of datasets. The experimental procedure included a daily sleep quality survey conducted prior to the morning session. This was succeeded by the VAS-F questionnaire, a Choice Reaction Time (CRT) task, reading a text in a scientific style, performing the \"Landolt rings\" correction test, playing the \"Tetris\" game, and a second CRT. The latter was incorporated at the discretion of the authors, cognizant of the potential variability in operator fatigue levels between the inception and termination of the recording session. The aggregate duration of such sessions, on average, approximated one hour. Throughout the Choice Reaction Time (CRT) assessment, a comprehensive group of parameters was recorded, such as the average reaction time, its standard deviation, and the number of errors made by participants during task performance. Participants engaged in the reading of scientific-style text, which can be a typical work-related activity. This task served as a static cognitive load task aimed at evaluating cognitive performance. The Landolt rings correction test is a well-established method for evaluating visual acuity. Based on [13], the following parameters were recorded during the Landolt rings test:  
1. Time spent (_t_). 2.