Assessing low-back loading during lifting using personalized electromyography-driven trunk models and NIOSH-based...

Area of Science:

• Occupational Biomechanics
• Ergonomics
• Musculoskeletal Modeling

Background:

• Workplace injuries from physically demanding tasks, like lifting, are a significant concern.
• Current ergonomic assessments, such as the Revised NIOSH Lifting Equation (RNLE), estimate low-back loading risks.
• Advances in musculoskeletal modeling allow for personalized, physiologically valid estimations of biomechanical loads.

Purpose of the Study:

• To compare the risk assessment capabilities of the Revised NIOSH Lifting Equation (RNLE) and personalized musculoskeletal models (pEMS).
• To evaluate low-back loading during various lifting tasks using both RNLE and pEMS.
• To determine if lumbosacral compressive loads are a superior indicator of risk.

Main Methods:

• Seven healthy participants performed lifting tasks at different risk levels.
• Risk and low-back loading were assessed using both the RNLE and pEMS.
• pEMS utilized surface electromyography and joint angle data to estimate lumbosacral joint loads.

Main Results:

• pEMS-estimated biomechanical loads aligned with RNLE-defined risk levels.
• However, pEMS indicated higher compressive and shear loads at the lumbosacral joint than RNLE limits.
• Lumbosacral compressive loads demonstrated potential as a more precise risk demarcation parameter.

Conclusions:

• Personalized musculoskeletal models provide detailed biomechanical insights into lifting tasks.
• Current ergonomic guidelines may underestimate the actual low-back loading experienced during demanding tasks.
• Further research with diverse populations and wearable sensors is recommended for personalized workplace risk assessment and musculoskeletal health monitoring.