Archery ranks among the sports with a high incidence of upper extremity injuries, particularly affecting the drawing shoulder and elbow, as well as inducing stress on the lower back. This study seeks to bridge the gap by integrating real-time human motion with biomechanical software to enhance the ergonomics of archers. Thirteen participants were involved in four tasks, using different bows with varied draw weights and shooting distances. Through the application of advanced integrative technology, this study highlights the distinct postures adopted by both males and females, which indicate the biomechanical differences between genders. Additionally, an analysis of the correlation between exposed spinal forces and these adopted postures provides insights into injury risk assessment during the key archery movements. The findings of this study have the potential to significantly enhance the application of training methodologies and the design of assistive devices. These improvements are geared towards mitigating injury risks and enhancing the overall performance of archers.

The objective of this study was to assess the accuracy of virtual reality (VR) technology in replicating real-life environments for the adoption of appropriate human postures and forces. Despite the widespread implementation of VR in various applications, there is a lack of research evaluating the accuracy of human postures and sensory aspects in the VR environment compared to real-life scenarios. A total of twenty-two student participants were recruited for this study, which involved a common lifting task. Two specific poses were identified as having potentially excessive forces exerted on the lower back. By comparing the angles of seven anatomical joints in both the real environment and the VR environment at each pose, we observed that depth perception may influence posture adoption in the VR setting. Moreover, the presence of a physical load applied to both hands significantly influenced the postures adopted by participants compared to those in the VR environment. These deviations in postures directly led to significant differences in predicted spinal forces exerted on the lower back, which in turn could result in inaccurate assessments of injury risks and the design of injury prevention programs. Therefore, it is crucial to understand the accuracy of VR technology as a substitute for real-life environments.

Archery has increasingly captivated attention in its use for rehabilitation and physical education due to its adaptability for various abilities. However, this repetitive sport carries some injury risk in the shoulder, elbow, and back during the draw and release phases. While research often explores factors affecting shooting performance, limited studies have examined the interplay between gender-specific biomechanics and bow-related variables on lumbar stress and shooting mechanics. This study addresses this gap by leveraging the Xsens MVN Awinda motion capture system and JACK Siemens ergonomic software to analyze full-body movements of archers with different experience levels, bow types, and target placements. Thirteen subjects participated in this investigation, each equipped with standard gear. We analyzed their posture throughout the shooting sequence and the forces acting on their lower back. This innovative approach streamlines data collection and eliminates the need for extensive prototyping. Our findings highlight natural biomechanical adaptations between males and females when using bows of varying draw weights. Males generally exhibited greater consistency and stability, while females showed increased variability, particularly with heavier bows. This research establishes a foundation for ergonomic and reproducible archery techniques, enabling individualized training and performance optimization strategies.

Background: Healthcare professionals are at significant risk of musculoskeletal injuries due to the physically demanding nature of patient-handling tasks. While various ergonomic interventions have been introduced to mitigate these risks, comprehensive methods for assessing and addressing musculoskeletal hazards remain limited. Purpose: This study presents a novel approach to evaluating musculoskeletal injury risks among healthcare workers, marking the first instance in which two motion tracking systems are used simultaneously. This dual-system setup enables a more comprehensive and dynamic analysis of worker interactions in real time. Healthcare professionals were divided into three groups to perform patient transfer tasks. Three key poses within the task, associated with peak lumbar forces, were identified and analyzed. Results: The resulting compressive forces on the participants’ lower back ranged from 581.0 N to 3589.1 N, and the Anterior–Posterior (A/P) shear forces ranged from 33.1 N to 912.3 N across the three poses. Relative differences in trunk flexion showed strong correlations with compressive and A/P shear forces at each pose, respectively. Discussion and conclusion: Strong associations were found between lumbar loads and participant’s anthropometrics. Recommendations for optimal postures and partner pairings were developed to help reduce the risk of lower back injuries during patient handling.

Manual lifting is a common occupational activity associated with an increased risk of low back disorders. In this study, 22 participants from UPMC Hamot, organized into 11 pairs, were recruited. A combination of motion capture techniques and an injury assessment tool was used to investigate the relationships among body anthropometrics, three-dimensional trunk and lower-limb kinematics, and lumbar spinal loading. Potential differences in lifting mechanics were observed between male and female participants. Males exhibited greater trunk flexion and higher compressive loading, while females demonstrated greater hip and knee flexion with reduced trunk motion. These findings indicate that spinal loading during lifting is influenced by an interaction between anthropometric characteristics and movement coordination patterns, with variable behavioral trends affecting load distribution across the trunk and lower extremities. The results provide biomechanical insight that may inform the development of bio-ergonomic training techniques aimed at reducing lumbar spine loading and minimizing injury risk in occupational lifting tasks.

Emergency responders face a high risk of musculoskeletal disorders (MSDs), particularly lower back injuries, due to frequent patient-handling tasks performed in awkward and dynamic postures. This aim of study is to utilize dual motion capture systems integrated with a digital human modeling (DHM) ergonomics tool to evaluate the biomechanical effects of two common two-person carrying techniques: facing forward and facing each other. Twenty-two participants lifted a 25 kg mannequin while wearing Xsens motion sensors, and lumbar forces and joint angles were analyzed using Siemens Jack software (v9.0). Peak compressive and anterior–posterior (AP) shear forces, along with trunk, hip, and knee joint angles, were examined. Compressive forces ranged from approximately 948.6 to 2955.6 N, and AP shear forces ranged from 286.0 to 827.0 N. Mean compressive and AP shear forces were higher during the facing-each-other task (1977.3 N and 595.0 N) than during the facing-forward task (1596.0 N and 462.0 N). Males experienced higher spinal loads than females across both tasks. The facing-each-other technique was associated with greater hip flexion, lower knee flexion, and reduced trunk flexion, whereas the facing-forward technique resulted in less hip flexion, greater knee flexion, and greater trunk flexion. Overall, under the conditions of the present study, the facing-forward technique was associated with lower lumbar loading indicators. Integrating motion capture with DHM offers a valuable approach for evaluating realistic rescue tasks and can inform ergonomic training strategies for emergency responders.