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A Universal Model of the Lumbar Back Muscles in the Upright Position

Bogduk, Nikolai, Macintosh, Janet E., Pearcy, Mark J.·1992·Spine

Abstract

A model of the lumbar back muscles was constructed incorporating 49 fascicles of the lumbar erector spinae and multifidus. The attachment sites and sizes of fascicles were based on previous anatomic studies, and the fascicles were modeled on radiographs of nine normal volunteers in the upright position. Calculations revealed that the thoracic fibers of the lumbar erector spinae contribute 50% of the total extensor moment exerted on L4 and L5; multifidus contributes some 20%; and the remainder is exerted by the lumbar fibers of erector spinae. At upper lumbar levels, the thoracic fibers of the lumbar erector spinae contribute between 70% and 86% of the total extensor moment. In the upright posture, the lumbar back muscles exert a net posterior shear force on segments L1 to L4, but exert an anterior shear force on L5. Collectively, all the back muscles exert large compression forces on all segments. A force coefficient of 46 Ncm-2 was determined to apply for the back muscles. These results have a bearing on the appreciation of the effects on the back muscles of surgery and physiotherapy.

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Metadata

Authors
Bogduk, N., Macintosh, J. E., & Pearcy, M. J.
Venue
Spine
Published
1992-08
Volume
17
Issue
8
Pages
897-913
ISSN
0362-2436 (ISSN-L)
OpenAlex
W1977085034
Cited by
371
References
0
FWCI
3.20
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A Universal Model of the Lumbar Back Muscles in the Upright Position. https://app.cochat.ai/papers/10.1097/00007632-199208000-00007
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Bogduk, N., Macintosh, J. E., & Pearcy, M. J. (1992). A Universal Model of the Lumbar Back Muscles in the Upright Position. Spine. https://doi.org/10.1097/00007632-199208000-00007

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.