Estimation of Patient Specific Lumbar Spine Muscle Forces Using Multi-physical Musculoskeletal Model and Dynamic MRI

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 245)


Trunk muscle forces are of great interest in the diagnosis and treatment of low back pain diseases. Musculoskeletal modeling is often used to estimate muscle forces using optimization principle. Available parameterized multibody lumbar spine models used generic geometries and literature-based values leading to inaccurate muscle architecture and muscle forces not reliable for a specific case. In this present study, a multi-physical musculoskeletal model of the lumbar spine was developed from medical imaging to estimate patient specific trunk muscle forces with lumbar spine range of motions derived from dynamic MRI data in supine position. As results, a 3D patient specific musculoskeletal model was developed with 126 muscle fascicles. Maximal estimated forces of all muscle groups range from 3 to 40 N for hyperlordosis motion. The higher muscle forces were estimated in iliocostalis lumborum pars lumborum. This study has demonstrated that patient specific modeling is essential for clinical analysis of lumbar spine.


Lumbar Spine Muscle Force Dynamic Magnetic Resonance Image Muscle Fascicle Musculoskeletal Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Adams, M.A.: Biomechanics of back pain. Acupunct. Med. 22(4), 178–188 (2004)CrossRefGoogle Scholar
  2. 2.
    Norris, C.M.: Spinal Stabilisation: Limiting Factors to End-range Motion in the Lumbar Spine. Physiotherapy 81(2), 64–72 (1995)CrossRefGoogle Scholar
  3. 3.
    Haynes, W.: New strategies in the treatment and rehabilitation of the lumbar spine. Journal of Bodywork and Movement Therapies 7(2), 117–130 (2003)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Périé, D., Sales De Gauzy, J., Ho Ba Tho, M.C.: Biomechanical evaluation of Cheneau-Toulouse-Munster brace in the treatment of scoliosis using optimisation approach and finite element method. Med. Biol. Eng. Comput. 40(3), 296–301 (2002)CrossRefGoogle Scholar
  5. 5.
    Noailly, J., Wilke, H.J., Planell, J.A., Lacroix, D.: How does the geometry affect the internal biomechanics of a lumbar spine bi-segment finite element model? Consequences on the validation process. Journal of Biomechanics 40(11), 2414–2425 (2007)CrossRefGoogle Scholar
  6. 6.
    Schmidt, H., Shirazi-Adl, A., Galbusera, F., Wilke, H.J.: Response analysis of the lumbar spine during regular daily activities-A finite element analysis. Journal of Biomechanics 43(10), 1849–1856 (2010)CrossRefGoogle Scholar
  7. 7.
    Schmidt, H., Reitmaier, S.: Is the ovine intervertebral disc a small human one?: A finite element model study. Journal of the Mechanical Behavior of Biomedical Materials 17, 229–241 (2013)CrossRefGoogle Scholar
  8. 8.
    Schroeder, Y., Sivan, S., Wilson, W., Merkher, Y., Huyghe, J., Maroudas, A., Baaijens, F.P.T.: Are disc pressure, stress, and osmolarity affected by intra and extra fibrillar fluid exchange? Journal of Orthopaedic Research 25, 1317–1324 (2007)CrossRefGoogle Scholar
  9. 9.
    Alicia, R.J., Chun-Yuh, H., Wei, Y.G.: Effect of endplate calcification and mechanical deformation on the distribution of glucose in intervertebral disc: a 3D finite element study. Computer Methods in Biomechanics and Biomedical Engineering 14(2), 195–204 (2011)CrossRefGoogle Scholar
  10. 10.
    Erdemir, A., McLean, S., Herzog, W., van den Bogert, A.J.: Model-based estimation of muscle forces exerted during movements. Clin. Biomech. 22(2), 131–154 (2007)CrossRefGoogle Scholar
  11. 11.
    de Zee, M., Hansen, L., Wong, C., Rasmussen, J., Simonsen, E.B.: A generic detailed rigid-body lumbar spine model. Journal of Biomechanics 40(6), 1219–1227 (2007)CrossRefGoogle Scholar
  12. 12.
    Christophy, M., Faruk Senan, N.A., Lotz, J.C., O’Reilly, O.M.: A musculoskeletal model for the lumbar spine. Biomech. Model Mechanobiol. 11(1-2), 19–34 (2012)CrossRefGoogle Scholar
  13. 13.
    Han, K.S., Zander, T., Taylor, W.R., Rohlmann, A.: An enhanced and validated generic thoraco-lumbar spine model for prediction of muscle forces. Medical Engineering and Physics 34(6), 709–716 (2012)CrossRefGoogle Scholar
  14. 14.
    Huynh, K.T., Gibson, I., Lu, W.F., Jagdish, B.N.: Simulating dynamics of thoracolumbar spine derived from LifeMOD under haptic forces. World Academy of Science, Engineering and Technology 64, 278–285 (2010)Google Scholar
  15. 15.
    Stokes, I.A.F., Gardner-Morse, M.: Lumbar spine maximum efforts and muscle recruitment patterns predicted by a model with multijoint muscles and flexible joints. J. Biomech. 28(2), 173–186 (1995)CrossRefGoogle Scholar
  16. 16.
    Dao, T.T., Marin, F., Pouletaut, P., Aufaure, P., Charleux, F., Ho Ba Tho, M.C.: Estimation of Accuracy of Patient Specific Musculoskeletal Modeling: Case Study on a Post-Polio Residual Paralysis Subject. Computer Method in Biomechanics and Biomedical Engineering 15 (7), 745–751 (2012)CrossRefGoogle Scholar
  17. 17.
    Gagnon, D., Arjmand, N., Plamondon, A., Shirazi-Adl, A., Lariviére, C.: An improved multi-joint EMG-assisted optimization approach to estimate joint and muscle forces in a musculoskeletal model of the lumbar spine. Journal of Biomechanics 44(8), 1521–1529 (2011)CrossRefGoogle Scholar
  18. 18.
    Delp, S.L., Anderson, F.C., Arnold, A.S., Loan, P., Habib, A., John, C.T., Guendelman, E., Thelen, D.G.: OpenSim: Open-source Software to Create and Analyze Dynamic Simulations of Movement. IEEE Transactions on Biomedical Engineering 54(11), 1940–1950 (2007)CrossRefGoogle Scholar
  19. 19.
    Pearcy, M.J., Bogduk, N.: Instantaneous axes of rotation of the lumbar intervertebral joints. Spine 13, 1033–1041 (1998)CrossRefGoogle Scholar
  20. 20.
    Wu, G., Siegler, S., Allard, P., Kirtley, C., Leardini, A., Rosenbaum, D., Whittle, M., D’Lima, D.D., Cristofolini, L., Witte, H., Schmid, O., Stokes, I.: ISB recommendation on definitions of joint coordinate system of various joints for the reporting of human joint motion–part I: ankle, hip, and spine. J. Biomech. 35(4), 543–548 (2002)CrossRefGoogle Scholar
  21. 21.
    Hill, A.V.: The heat of shortening and dynamics constants of muscles. Proc. R. Soc. Lond. B 126(843), 136–195 (1938)CrossRefGoogle Scholar
  22. 22.
    Schultz, A., Andersson, G., Ortengren, R., Haderspeck, K., Nachemson, A.: Loads on the lumbar spine. Validation of a biomechanical analysis by measurements of intradiscal pressures and myoelectric signals. J. Bone Joint Surg. Am. 64, 713–720 (1982)Google Scholar
  23. 23.
    Blemker, S.S., Asakawa, D.S., Gold, G.E., Delp, S.L.: Image-based musculskeletal modeling: Applications, advances, and future opportunities. Journal of Magnetic Resonance Imaging 25, 441–451 (2007)CrossRefGoogle Scholar
  24. 24.
    Bensamoun, S.F., Dao, T.T., Charleux, F., Ho Ba Tho, M.C.: Calculation of in vivo muscle forces derived from MR elastography. Journal of Biomechanics 45(1), S489 (2012)Google Scholar
  25. 25.
    Buchanan, T.S., Lloyd, D.G., Manal, K., Besier, T.F.: Neuromusculoskeletal modeling: estimation of muscle forces and joint moments and movements from measurements of neural command. Journal of Applied Biomechanics 20(4), 367–395 (2004)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.UTC CNRS UMR 7338, Biomechanics and Bioengineering (BMBI)University of Technology of CompiègneCompiègne cedexFrance
  2. 2.ACRIM-Polyclinique St CômeCompiègne CedexFrance
  3. 3.National Center for Spinal DisordersBuda Health CenterBudapestHungary

Personalised recommendations