An Enhanced Planar Linked Segment Model for Predicting Lumbar Spine Loads during Symmetric Lifting Tasks

Author:

Picerno PietroORCID

Abstract

The present technical note aimed at enriching the planar linked segment model originally proposed by Chaffin with the prediction of the moment arm and of the orientation of the line of action of the back extensor muscles during symmetric lifting tasks. The prediction equations proposed by van Dieen and de Looze for their single equivalent muscle model were used for such a purpose. Their prediction was based on the thorax-to-pelvis flexion angle as computed from 3D video-based motion capture. In order to make these prediction equations compliant with a two-dimensional analysis, the planar angle formed by the segment joining L5/S1 to the shoulder with the longitudinal axis of the pelvis was introduced. This newly computed planar trunk flexion angle was used to feed van Dieen and de Looze’s equations, comparing the results with the original model. A full-body Plug-in-Gait model relative to 10 subjects performing manual lifting activities using a stoop and a squat technique was used for model validation. A strong association was found between the proposed planar trunk flexion angle and that used by van Dieen and de Looze (r = 0.970). A strong association and a high level of agreement were found between the back extensor muscle moment arm (r = 0.965; bias < 0.001 m; upper limit of agreement (LOA) = 0.002 m; lower LOA < 0.001 m) and the orientation of the line of action (r = 0.970; bias = 2.8°; upper LOA = 5.3°; lower LOA = 0.2°) as computed using the two methods. For both the considered variables, the prediction error fell within the model sensitivity.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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