Frontal plane pelvic kinematics during high velocity running: Association with hamstring injury history.

INTRODUCTION: Hamstring injuries are the most prevalent non-contact soft tissue injury in sports, with a larger portion of injuries being recurrent. The sagittal plane running kinematics correlated to hamstring injury history has been well documented. However, analysis of frontal plane kinematics allows for observation of stability and symmetry. This study aimed to examine the frontal plane running kinematics of elite collegiate level sprinters, with and without previous hamstring injury, compared to healthy counterparts. METHODS: Thirty-nine participants performed three 50-m sprints, with three inertial measurement unit sensors placed on the pelvis: one on each iliac crest and one on the sacrum. Participants were classified based on sex, competitive status, and injury history. To investigate differences based on group classification, the data were used to analyze mediolateral motion (relative magnitude of mediolateral acceleration) and asymmetry (difference in acceleration between right and left iliac crests) during each stance phase throughout the run. RESULTS: Injured sprinters displayed significantly greater mediolateral motion and asymmetry during stances than healthy counterparts. CONCLUSIONS: This study demonstrates that frontal plane running stance dynamics are different in athletes with previous hamstring injury than healthy athletes. These athletes may benefit from rehabilitation strategies targeting postural control and stability during dynamic tasks.

How Accurately Can Wearable Sensors Assess Low Back Disorder Risks during Material Handling? Exploring the Fundamental Capabilities and Limitations of Different Sensor Signals.

Low back disorders (LBDs) are a leading occupational health issue. Wearable sensors, such as inertial measurement units (IMUs) and/or pressure insoles, could automate and enhance the ergonomic assessment of LBD risks during material handling. However, much remains unknown about which sensor signals to use and how accurately sensors can estimate injury risk. The objective of this study was to address two open questions: (1) How accurately can we estimate LBD risk when combining trunk motion and under-the-foot force data (simulating a trunk IMU and pressure insoles used together)? (2) How much greater is this risk assessment accuracy than using only trunk motion (simulating a trunk IMU alone)? We developed a data-driven simulation using randomized lifting tasks, machine learning algorithms, and a validated ergonomic assessment tool. We found that trunk motion-based estimates of LBD risk were not strongly correlated (r range: 0.20-0.56) with ground truth LBD risk, but adding under-the-foot force data yielded strongly correlated LBD risk estimates (r range: 0.93-0.98). These results raise questions about the adequacy of a single IMU for LBD risk assessment during material handling but suggest that combining an IMU on the trunk and pressure insoles with trained algorithms may be able to accurately assess risks.

An ergonomic assessment tool for evaluating the effect of back exoskeletons on injury risk.

Low back disorders (LBDs) are a leading injury in the workplace. Back exoskeletons (exos) are wearable assist devices that complement traditional ergonomic controls and reduce LBD risks by alleviating musculoskeletal overexertion. However, there are currently no ergonomic assessment tools to evaluate risk for workers wearing back exos. Exo-LiFFT, an extension of the Lifting Fatigue Failure Tool, is introduced as a means to unify the etiology of LBDs with the biomechanical function of exos. We present multiple examples demonstrating how Exo-LiFFT can assess or predict the effect of exos on LBD risk without costly, time-consuming electromyography studies. For instance, using simulated and real-world material handling data we show an exo providing a 30 Nm lumbar moment is projected to reduce cumulative back damage by ∼70% and LBD risk by ∼20%. Exo-LiFFT provides a practical, efficient ergonomic assessment tool to assist safety professionals exploring back exos as part of a comprehensive occupational health program.