Evaluation of a geometry-based knee joint compared to a planar knee joint

Abstract

Today neuromuscular simulations are used in several fields, such as diagnostics and planing of surgery, to get a deeper understanding of the musculoskeletal system. During the last year, new models and datasets have been presented which can provide us with more in-depth simulations and results. The same kind of development has occurred in the field of studying the human knee joint using complex three dimensional finite element models and simulations. In the field of musculoskeletal simulations, no such knee joints can be used. Instead the most common knee joint description is an idealized knee joint with limited accuracy or a planar knee joint which only describes the knee motion in a plane. In this paper, a new knee joint based on both equations and geometry is introduced and compared to a common clinical planar knee joint. The two kinematical models are analyzed using a gait motion, and are evaluated using the muscle activation and joint reaction forces which are compared to in-vivo measured forces. We show that we are able to predict the lateral, anterior and longitudinal moments, and that we are able to predict better knee and hip joint reaction forces.

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References

  1. 1.

    Allaire, S., Jacq, J.-J., Burdin, V., Roux, C.: Ellipsoid-constrained robust fitting of quadrics with application to the 3d morphological characterization of articular surfaces. In: Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, Aug. 2007, pp. 5087–5090 (2007)

    Google Scholar 

  2. 2.

    Anderson, F.C., Pandy, M.G.: Static and dynamic optimization solutions for gait are practically equivalent. J. Biomech. 34(2), 153–161 (2001)

    Article  Google Scholar 

  3. 3.

    Arnold, E., Ward, S., Lieber, R., Delp, S.: A model of the lower limb for analysis of human movement. Ann. Biomed. Eng. 38, 269–279 (2010). doi:10.1007/s10439-009-9852-5

    Article  Google Scholar 

  4. 4.

    Bergmann, G., Deuretzbacher, G., Heller, M., Graichen, F., Rohlmann, A., Strauss, J., Duda, G.N.: Hip contact forces and gait patterns from routine activities. J. Biomech. 34(7), 859–871 (2001)

    Article  Google Scholar 

  5. 5.

    Castagno, P., Richards, J., Freenan, M., Lennon, N.: Comparison of 3-dimensional lower extremity kinematics during walking gait using two different marker sets. Gait Posture 3(2), 87–87 (1995)

    Article  Google Scholar 

  6. 6.

    Damsgaard, M., Rasmussen, J., Christensen, S.T., Surma, E., de Zee, M.: Analysis of musculoskeletal systems in the anybody modeling system. Simul. Model. Pract. Theory 14(8), 1100–1111 (2006). SIMS 2004

    Article  Google Scholar 

  7. 7.

    Delp, S.L., Loan, J.P., Hoy, M.G., Zajac, F.E., Topp, E.L., Rosen, J.M.: An interactive graphics-based model of the lower extremity to study orthopaedic surgical procedures. IEEE Trans. Biomed. Eng. 37(8), 757–767 (1990)

    Article  Google Scholar 

  8. 8.

    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 Trans. Biomed. Eng. 54(11), 1940–1950 (2007)

    Article  Google Scholar 

  9. 9.

    DLima, D.D., Patil, S., Steklov, N., Chien, Shu, Colwell, C.W. Jr.: In vivo knee moments and shear after total knee arthroplasty. J. Biomech. 40(Suppl. 1), S11–S17 (2007). Interaction of Mechanics and Biology in Knee Joint Restoration and Regeneration

    Article  Google Scholar 

  10. 10.

    Ellis, B.J., Lujan, T.J., Dalton, M.S., Weiss, J.A.: Medial collateral ligament insertion site and contact forces in the acl-deficient knee. J. Orthop. Res. 24(4), 800–810 (2006)

    Article  Google Scholar 

  11. 11.

    Fernandez, J., Hunter, P.: An anatomically based patient-specific finite element model of patella articulation: towards a diagnostic tool. Biomech. Model. Mechanobiol. 4, 20–38 (2005). doi:10.1007/s10237-005-0072-0

    Article  Google Scholar 

  12. 12.

    Glitsch, U., Baumann, W.: The three-dimensional determination of internal loads in the lower extremity. J. Biomech. 30(11–12), 1123–1131 (1997)

    Article  Google Scholar 

  13. 13.

    De Groote, F., De Laet, T., Jonkers, I., De Schutter, J.: Kalman smoothing improves the estimation of joint kinematics and kinetics in marker-based human gait analysis. J. Biomech. 41(16), 3390–3398 (2008)

    Article  Google Scholar 

  14. 14.

    Heinlein, B., Kutzner, I., Graichen, F., Bender, A., Rohlmann, A., Halder, A.M., Beier, A., Bergmann, G.: Complete data of total knee replacement loading for level walking and stair climbing measured in vivo with a follow-up of 6–10 months. Clin. Biomech. 24(4), 315–326 (2009)

    Article  Google Scholar 

  15. 15.

    Horsman, K.: The Twente lower extremity model. PhD thesis, Department of Engineering Technology, University of Twente, Netherlands (2007)

  16. 16.

    Moro-oka, T.A., Hamai, S., Miura, H., Shimoto, T., Higaki, H., Fregly, B.J., Iwamoto, Y., Banks, S.A.: Dynamic activity dependence of in vivo normal knee kinematics. J. Orthop. Res. 26(4), 428–462 (2007)

    Article  Google Scholar 

  17. 17.

    Morrison, J.B.: Function of the knee joint in various activities. Biomed. Eng. 4, 573–580 (1969)

    MathSciNet  Google Scholar 

  18. 18.

    Kadaba, M.P., Ramakrishnan, H.K., Wootten, M.E., Gainey, J., Gorton, G., Cochran, G.V.: Repeatability of kinematic, kinetic, and electromyographic data in normal adult gait. J. Orthop. Res. 7(6), 849–860 (1989)

    Article  Google Scholar 

  19. 19.

    Kalman, R.E.: A new approach to linear filtering and prediction problems. Trans. ASME, J. Basic Eng. 82, 35–45 (1960)

    Google Scholar 

  20. 20.

    Kurosawa, H., Walker, P.S., Abe, S., Garg, A., Hunter, T.: Geometry and motion of the knee for implant and orthotic design. J. Biomech. 18(7), 487–491, 493–499 (1985)

    Article  Google Scholar 

  21. 21.

    Kutzner, I., Heinlein, B., Graichen, F., Bender, A., Rohlmann, A., Halder, A., Beier, A., Bergmann, G.: Loading of the knee joint during activities of daily living measured in vivo in five subjects. J. Biomech. 43(11), 2164–2173 (2010)

    Article  Google Scholar 

  22. 22.

    Liu, M.Q., Anderson, F.C., Schwartz, M.H., Delp, S.L.: Muscle contributions to support and progression over a range of walking speeds. J. Biomech. 41(15), 3243–3252 (2008)

    Article  Google Scholar 

  23. 23.

    Pioletti, D.P., Rakotomanana, L.R., Benvenuti, J.F., Leyvraz, P.F.: Viscoelastic constitutive law in large deformations: application to human knee ligaments and tendons. J. Biomech. 31(8), 753–757 (1998)

    Article  Google Scholar 

  24. 24.

    Ramaniraka, N.A., Saunier, P., Siegrist, O., Pioletti, D.P.: Biomechanical evaluation of intra-articular and extra-articular procedures in anterior cruciate ligament reconstruction: a finite element analysis. Clin. Biomech. 22(3), 336–343 (2007)

    Article  Google Scholar 

  25. 25.

    Sandholm, A., Pronost, N., Thalmann, D.: Motionlab: a matlab toolbox for extracting and processing experimental motion capture data for neuromuscular simulations. In: Magnenat-Thalmann, N. (ed.) Modelling the Physiological Human. Lecture Notes in Computer Science, vol. 5903, pp. 110–124. Springer, Berlin (2009)

    Google Scholar 

  26. 26.

    Schmid, J., Magnenat-Thalmann, N.: MRI bone segmentation using deformable models and shape priors. Med. Image Comput. Comput. Assist. Interv., 119–126 (2008)

  27. 27.

    Schmid, J., Sandholm, A., Chung, F., Thalmann, D., Delingette, H., Magnenat-Thalmann, N.: Musculoskeletal simulation model generation from MRI data sets and motion capture data. In: Magnenat-Thalmann, Nadia, Zhang, J.J.J., Feng, D.D.D. (eds.) Recent Advances in the 3D Physiological Human, pp. 3–19. Springer, London (2009)

    Google Scholar 

  28. 28.

    Taylor, W.R., Heller, M.O., Bergmann, G., Duda, G.N.: Tibio-femoral loading during human gait and stair climbing. J. Orthop. Res. 22(3), 625–632 (2004)

    Article  Google Scholar 

  29. 29.

    Thelen, D.G., Anderson, F.C.: Using computed muscle control to generate forward dynamic simulations of human walking from experimental data. J. Biomech. 39(6), 1107–1115 (2006)

    Article  Google Scholar 

  30. 30.

    Walker, P.S., Rovick, J.S., Robertson, D.D.: The effects of knee brace hinge design and placement on joint mechanics. J. Biomech. 21(11), 965–967, 969–974 (1988)

    Article  Google Scholar 

  31. 31.

    Weiss, J.A., Maker, B.N., Govindjee, S.: Finite element implementation of incompressible, transversely isotropic hyperelasticity. Comput. Methods Appl. Mech. Eng. 135(1–2), 107–128 (1996)

    MATH  Article  Google Scholar 

  32. 32.

    Yamaguchi, G.T., Zajac, F.E.: A planar model of the knee joint to characterize the knee extensor mechanism. J. Biomech. 22(1), 1–10 (1989)

    Article  Google Scholar 

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Correspondence to Anders Sandholm.

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Sandholm, A., Schwartz, C., Pronost, N. et al. Evaluation of a geometry-based knee joint compared to a planar knee joint. Vis Comput 27, 161–171 (2011). https://doi.org/10.1007/s00371-010-0538-7

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Keywords

  • Knee joint
  • Inverse kinematics and dynamics
  • Joint reaction
  • Computed muscular control
  • OrthoLoad
  • Validation
  • Musculoskeletal model