Understanding low back muscle morphology is critical to understanding spinal loading and the underlying injury mechanisms, which help in characterizing risk and, therefore, minimize low back pain injuries. Individualized erector spinae muscle mass (ESMM) cross-sectional area (CSA) allows biomechanics practitioners to calculate individualized force generating capacities and spinal loadings for given tasks. The objective is to perform morphological analyses and then provide regression models to estimate the ESMM CSA of an individual with his/her subject characteristics. Thirty-five subjects (13 females and 22 males) without low back pain (LBP) history were included in this magnetic resonance imaging (MRI) study. Axial-oblique scans of low back region were used to measure the ESMM CSA. Subject demographics and anthropometrics were obtained and regressed over the ESMM CSA. Best-subset regression analyses were performed. Lean body mass (LBM) and the ankle, wrist, and head indexes were the most frequent predictive variables. Regression models with easy-to-measure variables showed smaller predictive power and increased estimation error compared to other regression models. Practitioners should consider this trade-off between model accuracy and complexity. An individual's ESMM CSA could be estimated by his/her individual characteristics, which enables biomechanical practitioners to estimate individualized low back force capacity and spinal loading.
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August 2019
Research-Article
Regression Models for the Erector Spinae Muscle Mass (ESMM) Cross-Sectional Area: Asymptomatic Populations
Celal Gungor,
Celal Gungor
Department of Forest Industrial Engineering,
Izmir Katip Celebi University,
Cigli, Izmir 35620, Turkey
e-mail: celal.gungor@ikc.edu.tr
Izmir Katip Celebi University,
Cigli, Izmir 35620, Turkey
e-mail: celal.gungor@ikc.edu.tr
1Corresponding author.
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Ruoliang Tang,
Ruoliang Tang
Department of Occupational Science and
Technology,
University of Wisconsin-Milwaukee,
Milwaukee, WI 53211
e-mail: tangr@uwm.edu
Technology,
University of Wisconsin-Milwaukee,
Milwaukee, WI 53211
e-mail: tangr@uwm.edu
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Richard F. Sesek,
Richard F. Sesek
Department of Industrial and Systems
Engineering,
Auburn University,
Auburn, AL 36849
e-mail: sesek@auburn.edu
Engineering,
Auburn University,
Auburn, AL 36849
e-mail: sesek@auburn.edu
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Gerard A. Davis,
Gerard A. Davis
Department of Industrial and Systems
Engineering,
Auburn University,
Auburn, AL 36849
e-mail: davisga@auburn.edu
Engineering,
Auburn University,
Auburn, AL 36849
e-mail: davisga@auburn.edu
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Sean Gallagher
Sean Gallagher
Department of Industrial and Systems
Engineering,
Auburn University,
Auburn, AL 36849
e-mail: seangallagher@auburn.edu
Engineering,
Auburn University,
Auburn, AL 36849
e-mail: seangallagher@auburn.edu
Search for other works by this author on:
Celal Gungor
Department of Forest Industrial Engineering,
Izmir Katip Celebi University,
Cigli, Izmir 35620, Turkey
e-mail: celal.gungor@ikc.edu.tr
Izmir Katip Celebi University,
Cigli, Izmir 35620, Turkey
e-mail: celal.gungor@ikc.edu.tr
Ruoliang Tang
Department of Occupational Science and
Technology,
University of Wisconsin-Milwaukee,
Milwaukee, WI 53211
e-mail: tangr@uwm.edu
Technology,
University of Wisconsin-Milwaukee,
Milwaukee, WI 53211
e-mail: tangr@uwm.edu
Richard F. Sesek
Department of Industrial and Systems
Engineering,
Auburn University,
Auburn, AL 36849
e-mail: sesek@auburn.edu
Engineering,
Auburn University,
Auburn, AL 36849
e-mail: sesek@auburn.edu
Gerard A. Davis
Department of Industrial and Systems
Engineering,
Auburn University,
Auburn, AL 36849
e-mail: davisga@auburn.edu
Engineering,
Auburn University,
Auburn, AL 36849
e-mail: davisga@auburn.edu
Sean Gallagher
Department of Industrial and Systems
Engineering,
Auburn University,
Auburn, AL 36849
e-mail: seangallagher@auburn.edu
Engineering,
Auburn University,
Auburn, AL 36849
e-mail: seangallagher@auburn.edu
1Corresponding author.
Manuscript received July 29, 2016; final manuscript received April 13, 2019; published online May 13, 2019. Assoc. Editor: Joel D. Stitzel.
J Biomech Eng. Aug 2019, 141(8): 081009 (8 pages)
Published Online: May 13, 2019
Article history
Received:
July 29, 2016
Revised:
April 13, 2019
Citation
Gungor, C., Tang, R., Sesek, R. F., Davis, G. A., and Gallagher, S. (May 13, 2019). "Regression Models for the Erector Spinae Muscle Mass (ESMM) Cross-Sectional Area: Asymptomatic Populations." ASME. J Biomech Eng. August 2019; 141(8): 081009. https://doi.org/10.1115/1.4043558
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