Estimation of Spinal Loading During Manual Materials Handling Using Inertial Motion Capture

Area of Science:

• Biomechanics
• Occupational Health
• Ergonomics

Background:

• Traditional musculoskeletal modeling relies on lab-based motion capture and force plates, limiting field applications.
• Advances in inertial motion capture (IMC) and GRF prediction enable real-world data acquisition.
• Accurate estimation of lumbar spine loading during manual materials handling is crucial for injury prevention.

Purpose of the Study:

• To evaluate the concurrent validity of a novel methodology for estimating lumbar spine dynamic loading.
• To assess a musculoskeletal model driven solely by IMC data and predicted ground reaction forces and moments (GRF&Ms).
• To compare field-based estimations with traditional lab-based measurements during manual materials handling tasks.

Main Methods:

• A novel methodology used IMC data and predicted GRF&Ms to drive a musculoskeletal model.
• Compared L4-L5 joint reaction forces (JRFs) and erector spinae muscle forces with a model using marker-based motion capture and force plate data.
• 13 subjects performed various lifting and transferring tasks, including symmetrical and asymmetrical lifts.

Main Results:

• Moderate to excellent correlations were found for L4-L5 axial compression and erector spinae muscle forces.
• Low magnitude differences were observed for vertical ground reaction forces.
• Discrepancies were noted in trunk kinematics and L4-L5 shear forces between the two models.

Conclusions:

• The novel methodology is applicable for estimating relative L4-L5 axial compression forces during dynamic manual materials handling in the field.
• This approach offers a viable alternative to lab-based assessments for real-world ergonomic evaluations.
• Further refinement may be needed to improve accuracy for trunk kinematics and shear force estimations.