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

Frederik Greve Larsen, Frederik Petri Svenningsen, Michael Skipper Andersen, Mark de Zee, Sebastian Laigaard Skals

Research output: Contribution to journalJournal articleResearchpeer-review

5 Citations (Scopus)
18 Downloads (Pure)

Abstract

Musculoskeletal models have traditionally relied on measurements of segment kinematics and ground reaction forces and moments (GRF&Ms) from marked-based motion capture and floor-mounted force plates, which are typically limited to laboratory settings. Recent advances in inertial motion capture (IMC) as well as methods for predicting GRF&Ms have enabled the acquisition of these input data in the field. Therefore, this study evaluated the concurrent validity of a novel methodology for estimating the dynamic loading of the lumbar spine during manual materials handling based on a musculoskeletal model driven exclusively using IMC data and predicted GRF&Ms. Trunk kinematics, GRF&Ms, L4–L5 joint reaction forces (JRFs) and erector spinae muscle forces from 13 subjects performing various lifting and transferring tasks were compared to a model driven by simultaneously recorded skin-marker trajectories and force plate data. Moderate to excellent correlations and relatively low magnitude differences were found for the L4–L5 axial compression, erector spinae muscle and vertical ground reaction forces during symmetrical and asymmetrical lifting, but discrepancies were also identified between the models, particularly for the trunk kinematics and L4–L5 shear forces. Based on these results, the presented methodology can be applied for estimating the relative L4–L5 axial compression forces under dynamic conditions during manual materials handling in the field.
Original languageEnglish
JournalAnnals of Biomedical Engineering
Volume48
Issue number2
Pages (from-to)805-821
Number of pages17
ISSN0090-6964
DOIs
Publication statusPublished - 1 Feb 2020

Keywords

  • Inertial motion capture
  • Inverse dynamic analysis
  • Low back loading
  • Manual materials handling
  • Musculoskeletal modelling
  • Predicted ground reaction forces and moments

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