# Boosting Safety Protocol Compliance with Eye-Tracking in Chemical Plants
## 2 Materials and Methods  
The overall structure of this study is illustrated in Figure 1, which presents a four-phase research framework: literature-guided metric selection, experimental design and grouping, performance evaluation, and statistical analysis. The study began with a comprehensive literature review to identify cognitive and ergonomic principles relevant to XR-based safety training and to establish causal links between eye-tracking and key performance indicators. Based on these findings, five core metrics--reaction time, task accuracy, attention focus, error count, and corrective response time--were defined. In the second phase, the experiment was implemented using a VR platform with and without real-time eye-tracking feedback, dividing participants into control and experimental groups. The third phase evaluated the impact of gaze-directed feedback on situational awareness and hazard response under simulated industrial conditions. In the final phase, statistical analyses were performed to determine how eye-tracking integration influenced safety performance, cognitive engagement, and operational efficiency. Each of these phases is reflected in both the structure of Figure 1 and the following methodological sections.  
Subsequently, experimental validation was performed to assess the effectiveness of XR + eye-tracking training, using a controlled setup that simulated high-risk industrial safety scenarios. The following performance metrics were selected based on their relevance to the research goals:  
Reaction time: Assesses how quickly participants respond to safety stimuli (e.g., alarms), which is critical in emergency situations.  
Operational accuracy: Measures the correct execution of tasks, reflecting adherence to safety protocols.  
Attention focus: Indicates how effectively participants maintain focus on safety-critical elements.  
Error count: Tracks mistakes made during task execution, which directly correlates with safety performance.  
Corrective response time: Measures the speed of adaptation to real-time gaze feedback, highlighting the efficiency of the feedback loop in improving task performance.  
The gaze control system was integrated using the HTC SRanipal SDK (The HTC SRanipal SDK was developed by HTC Corporation, which is located in Taoyuan City, Taiwan, China.), which provided continuous gaze data. These data were transmitted to the Unity-based simulation environment, where gaze behavior was mapped to predefined safety-critical areas. When participants' gaze deviated from these areas, it was triggered within the simulation. The feedback loop was designed to guide users back to critical elements, ensuring that their attention was directed towards essential tasks and hazards. This dynamic gaze-tracking feedback was calibrated using Unity's event handling system, which processed gaze data to trigger corrective actions during the training simulation.  
The experimental design aimed to determine whether gaze-directed feedback enhances situational awareness, hazard recognition, and decision-making efficiency. The results obtained from the study were compared across different experience levels (experienced vs. inexperienced operators) to assess how training effectiveness varied between groups. This validation process provided empirical data to confirm the impact of visual attention monitoring on industrial safety training performance.