Literature DB >> 31748833

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

Frederik Greve Larsen1, Frederik Petri Svenningsen1, Michael Skipper Andersen2, Mark de Zee1, Sebastian Skals3,4.   

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.

Entities:  

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

Year:  2019        PMID: 31748833     DOI: 10.1007/s10439-019-02409-8

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  6 in total

Review 1.  A Systematic Review on Evaluation Strategies for Field Assessment of Upper-Body Industrial Exoskeletons: Current Practices and Future Trends.

Authors:  Pranav Madhav Kuber; Masoud Abdollahi; Mohammad Mehdi Alemi; Ehsan Rashedi
Journal:  Ann Biomed Eng       Date:  2022-08-02       Impact factor: 4.219

2.  A Promising Wearable Solution for the Practical and Accurate Monitoring of Low Back Loading in Manual Material Handling.

Authors:  Emily S Matijevich; Peter Volgyesi; Karl E Zelik
Journal:  Sensors (Basel)       Date:  2021-01-06       Impact factor: 3.576

3.  Back loading estimation during team handling: Is the use of only motion data sufficient?

Authors:  Antoine Muller; Philippe Corbeil
Journal:  PLoS One       Date:  2020-12-22       Impact factor: 3.240

Review 4.  Inertial Motion Capture-Based Wearable Systems for Estimation of Joint Kinetics: A Systematic Review.

Authors:  Chang June Lee; Jung Keun Lee
Journal:  Sensors (Basel)       Date:  2022-03-25       Impact factor: 3.576

5.  Biomechanical Analysis of Stoop and Free-Style Squat Lifting and Lowering with a Generic Back-Support Exoskeleton Model.

Authors:  Mark Tröster; Sarah Budde; Christophe Maufroy; Michael Skipper Andersen; John Rasmussen; Urs Schneider; Thomas Bauernhansl
Journal:  Int J Environ Res Public Health       Date:  2022-07-25       Impact factor: 4.614

6.  Inertial Motion Capture-Based Estimation of L5/S1 Moments during Manual Materials Handling.

Authors:  Antoine Muller; Hakim Mecheri; Philippe Corbeil; André Plamondon; Xavier Robert-Lachaine
Journal:  Sensors (Basel)       Date:  2022-08-26       Impact factor: 3.847

  6 in total

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