Agricultural work is associated with increased risk of adverse musculoskeletal health outcomes. The purpose of this study was to quantify exposure to biomechanical factors among a sample (n = 55) of farmers in the Midwest region of the U.S. while they performed a variety of routine agricultural activities, and to compare exposure levels between these activities. Surface electromyography was used to estimate activity levels of the erector spinae, upper trapezius, forearm flexor, and forearm extensor muscle groups. Simultaneously, inertial sensors were used to measure kinematics of the trunk, upper arm, and wrist. In general, lower muscle activity levels, less extreme postures, and slower movement speeds were observed during activities that involved primarily the use of agricultural machinery in comparison to manual activities, suggesting a potential advantage of mechanization relative to musculoskeletal health. Median wrist movement speeds exceeding recently proposed exposure thresholds were also observed during many manual activities, such as milking animals and repairing equipment. Upper arm postures and movement speeds did not appear to confer excessive risk for shoulder-related outcomes (on the whole), but interpretation of the results is limited by a sampling approach that may not have captured the full extent of exposure variation. Not surprisingly, substantial variation in exposure levels were observed within each agricultural activity, which is related to substantial variation in the equipment, tools, and work practices used by participants. Ultimately, the results of this study contribute to an emerging literature in which the physical demands of routine agricultural work have been described on the basis of sensor-based measurements rather than more common self-report or observation-based approaches.

Digital human modeling and simulation software has been identified as an effective tool for evaluating work tasks and design alternatives without requiring the expense of physical mock-ups and production trials. Despite recent commercial advancements and a broader availability of digital human modeling platforms, the peer-reviewed scientific literature lacks sufficient demonstration of the application of digital human modeling software within an occupational safety and health process for mitigating exposures to physical risk factors in a real-work environment. We describe the implementation of a commercially available digital human modeling platform as a component of an occupational safety and health process in a manufacturing environment over the course of 1 year. Success stories, challenges, and practical recommendations are discussed.

Exposure to whole-body vibration (WBV) is common among agricultural workers and is associated with musculoskeletal health outcomes such as low back pain. Little is known, however, about the characteristics of exposure experienced during actual production practices. We measured WBV levels during agricultural machinery use among a sample of farmers (n = 55) performing routine agricultural activities and explored machinery attributes that may explain WBV summary measures. We also measured trunk posture to provide additional information about physical exposures during machinery operation. Measurements were made on-farm and during actual work conditions of a sample of agricultural machines (n = 112), including tractors, combines, heavy utility vehicles, and all-terrain vehicles (ATVs). Results indicated the presence of high levels of vibration (median frequency-weighted root-mean-square acceleration of approximately 0.8 m s⁻²) with time signatures that include high-amplitude mechanical shocks (median crest factor of nearly 23). Compared to other machinery types, combines exhibited the lowest WBV levels and among the most favorable trunk postures. Substantial variability was observed in both the WBV and trunk posture summary measures, suggesting for future studies that alternative sampling strategies are needed to fully capture temporal patterns of machinery use.