## 4 Discussion  
This study introduces a novel quantitative approach for Work-Related Musculoskeletal Disorder (WMSD) risk assessment, integrating the three primary influencing factors--loading duration, human posture, and force/loading intensity [11]--to provide a more comprehensive and precise evaluation of occupational risks among aircraft maintenance personnel. The findings demonstrate that the proposed model effectively estimates actual human workloads and accurately predicts WMSD risks through 3D motion tracking, offering a reliable framework for ergonomic risk assessment in maintenance tasks. Compared to traditional methods such as questionnaires and physiological measurements [51; 52; 53], optical motion capture systems offer significant advantages in fatigue risk assessment due to their high precision and real-time capabilities. Questionnaire-based approaches, although widely applied, rely heavily on participants' subjective self-perception and recall, which can introduce bias and limit the accuracy of risk assessments [51; 52]. Moreover, previous studies have reported that physiological measurement techniques, while more objective, often exhibit relatively low reliability when compared to questionnaire-based approaches, especially in dynamic work settings [53]. In contrast, optical motion capture systems employ high-precision cameras to objectively and accurately track real-time changes in posture and joint movement throughout task execution. This enables a more comprehensive and reliable evaluation of physical workloads related to work-related WRMDs. By acknowledging and building upon these traditional methodologies, the novelty and contribution of our approach, grounded in dynamic motion analysis, are further emphasized. Figure 9: Comparison of model results with simulation results (The red line represents the normal operating probability result from the Jack software, while the green line represents the normal operating probability result from the model in this paper). This technology facilitates continuous monitoring of an individual's physical movements, collecting detailed data on gait, posture, movement speed, and angle variations. Unlike traditional methods, it eliminates subjective bias, providing a more objective and reliable assessment. Furthermore, optical motion capture systems can use 3D coordinate data to analyze the forces exerted on joints during the work process in depth. This allows for precise modeling of joint angles and forces, enabling the quantification and evaluation of how different postures impact joint load and muscle fatigue, leading to a more detailed health risk assessment. The 3D data analysis reveals potential sources of fatigue and identifies hazardous movements and improper postures that could lead to musculoskeletal problems. In highly collaborative tasks such as aircraft maintenance, it is difficult to accurately measure individual contributions, especially in terms of fatigue. While traditional subjective questionnaires may provide preliminary information on common injury sites within a group, they are limited in quantifying individual risks in complex work environments. This paper proposes an innovative comprehensive fatigue assessment model for aircraft maintenance work, aiming to address these limitations. Using motion capture technology, a rigid body chain structure of the human body is created to record joint movements and accurately capture 3D motion data of each joint. These data allow for precise calculation of joint trajectories and load levels, which can be aggregated over time to assess posture changes, joint loads, and potential risks at different time intervals. This approach provides a more objective and quantitative assessment of fatigue risk in physically demanding tasks, offering a stronger foundation for assessing work-related health risks. At the same time, the work of this paper still belongs to basic methodology research.