# Workload Assessment of Operators: Correlation Between NASA-TLX and Pupillary Responses
## 1 Introduction  
Operators in demanding environments such as surgery and driving often face challenging moments that place significant loads on their cognitive and physical resources [1, 2]. Workload, also known as cognitive load or mental workload, describes the mental and physical demands placed on an individual during task performance [3]. Excessive workload can impair performance, leading to negative outcomes like errors and accidents [4, 5]. This issue is particularly evident in imaging-guided tasks--such as visual tracking and endoscopic surgery--where individuals must process complex visual information in real time while making decisions or performing precise manual actions [6, 7]. Given the risk of cognitive overload in these demanding tasks, accurately measuring operator workload is essential for enhancing safety and efficiency. Traditional assessment tools like the NASA task load index (NASA-TLX) have been widely used and validated for measuring subjective perceptions of workload [8]. However, these tools have limitations: they are retrospective, rely on self-reporting, and can be influenced by personal biases. These shortcomings highlight the need for objective, real-time measures. To address this need, physiological signals offer a promising avenue for objective workload assessment. Among these, pupillary responses based on eye-tracking technologies have gained attention due to their sensitivity to cognitive load, feasibility for real-time monitoring, and cost-effectiveness [9]. Studies have linked pupillary responses with mental effort [10], and latterly with task complexity performed in the hand [11; 12]. However, how pupillary responses align with traditional self-report measures in imaging-guided tasks is not well documented. As a multimodal approach that combines subjective assessments with objective data gains popularity, understanding the consistency and correlation between these methods becomes increasingly important [13; 14]. Moreover, the task requirements behind different types of tasks and their repetition may affect workload levels differently. For instance, compared to a visual tracking task, performing a surgical procedure in the imaging-guided environment requires processing extensive visual input and delivering motor output with precision, potentially increasing the cognitive load on surgeon [15]. However, with repeated practice of a task, certain movements can become automated, potentially reducing workload [16]. Therefore, if our methods are sensitive in measuring workload changes, this study should yield differences in the workload metrics between different task types and repeated performances. This study aims to advance the understanding of workload assessment and make several key contributions:  
* Reveal a direct correlation between subjective workload measures (NASA-TLX) and objective indicators (pupillary responses) across two different imaging-guided tasks. This will validate pupil responses as a reliable measure of workload applicable to different task types;
* Reveal how tasks requiring both visual and motor coordination differ from those involving only visual tracking in terms of workload, as evidenced by both subjective and objective measures;
* Reveal the influence of repeated task exposure on workload, as evidenced by both subjective and objective measures. With objectives in mind, this study consisted of three main parts. First, this study examined the relationship between subjective workload scores, as measured by the NASA-TLX, and objective workload indicators derived from pupil responses during two different imaging-guided tasks. This study first hypothesizes that when individuals report higher subjective workload, they will also exhibit increased pupil dilation. Second, this study examines whether the workload differs between a routine visual tracking task and a more demanding visuomotor laparoscopic task that requires precise eye-hand coordination.