Clinical Gait Analysis and Musculoskeletal Modeling

  • Karelia TecanteEmail author
  • Frank Seehaus
  • Bastian Welke
  • Gavin Olender
  • Michael Schwarze
  • Sean Lynch
  • Christoph Hurschler


Gait analysis goal is to investigate the mechanics of the muscle, the relationships between muscles and bones and the motions of joints. However, for a deeper analysis of the internal force acting on the human body research has focused on multi-body modeling and simulation. The aim is to integrate the elements of the musculoskeletal system and the joint mechanics in order to better understand what has been learned through in vivo and in vitro experiments. This chapter presents a general overview of musculoskeletal modeling and simulation in the clinical gait area.


Musculoskeletal modeling Simulation In vitro In vivo Joint Muscle Kinematics Kinetics Segmentation 



This study was funded by the German Federal Ministry of Education and Research (BMBF AZ: 01EZ0775). The authors like to thank TU Berlin and Otto Bock Healthcare GmbH, Duderstadt, Germany for cooperation in TExoPro and EU Marie Curie Actions-Marie Curie Research Training Networks/ Multi-scale Biological Modalities for Physiological Human articulation 289897 (FP7-PEOPLE-2011-ITN) for their funding


  1. 1.
    Shihab, A., & Moataz, E. (2011). Development and validation of a three-dimensional biomechanical model of the lower extremity. In V. Klika (Ed.), Theoretical biomechanics. ISBN: 978-953-307-851-9, InTech, DOI: 10.5772/24156.
  2. 2.
    Erdemir, A., Scott M., Walter H., van den Bogert, A. J., et al. (2007). Model-based estimation of muscle forces exerted during movements. Clinical Biomechanics (Bristol, Avon), 22(2), 131–154.Google Scholar
  3. 3.
    Schwarze, M., Hurschler, C., Seehaus, F., Oehler, S., & Welke, B. (2013). Loads on the prosthesis-socket interface of above-knee amputees during normal gait: Validation of a multi-body simulation. Journal of Biomechanics, 46(6), 1201–1206.Google Scholar
  4. 4.
    Welke, B., Schwarze, M., Hurschler, C., Calliess, T., & Seehaus, F. (2013). Multi-body simulation of various falling scenarios for determining resulting loads at the prosthesis interface of transfemoral amputees with osseointegrated fixation. Journal of Orthopaedic Research, 31(7), 1123–1129.Google Scholar
  5. 5.
    Simon, S. R. (2004). Quantification of human motion: Gait analysis-benefits and limitations to its application to clinical problems. Journal of Biomechanics, 37(12), 1869–1880.Google Scholar
  6. 6.
    Hausdorff, J. M., Merit, E. C., Renée F., Jeanne Y. W., & Ary L. G. (1998). Gait variability and basal ganglia disorders: Stride-to-stride variations of gait cycle timing in parkinson’s disease and Huntington’s disease. Movement Disorders, 13(3), 428–437.Google Scholar
  7. 7.
    Hausdorff, J. M., Apinya, L., Merit, E. C., Amie, L. P., David, K., Ary, L. G., et al. (2000). Dynamic markers of altered gait rhythm in amyotrophic lateral sclerosis. Journal of Applied Physiology, 88(6), 2045–2053.Google Scholar
  8. 8.
    Hausdorff, J. M., Schaafsma, J. D., Balash, Y., Bartels, A. L., Gurevich, T., & Giladi, N. (2003). Impaired regulation of stride variability in Parkinson’s disease subjects with freezing of gait. Experimental Brain Research, 149(2), 187–194.Google Scholar
  9. 9.
    Bowen, J. D., & Gerry S. M. B. A. (2010). Gait Assessment. In The hip and pelvis in sports medicine and primary care (pp. 71–86). New York: Springer.Google Scholar
  10. 10.
    Klets, O., Riad, J. & Gutierrez-Farewik, E. M. (2010). Personalized musculoskeletal modeling of lower extremities based on magnetic resonance imaging data of 15 patients with hemiplegic cerebral palsy, IUTAM Symposium on human movement analysis and simulation, 2010 September 13th–15th, Belgium: Leuven.Google Scholar
  11. 11.
    Klets, O. (2011). Subject-specific musculoskeletal modeling of the lower extremities in persons with unilateral cerebral palsy. Licentiate dissertation. Stockholm: KTH Royal Institute of Technology.Google Scholar
  12. 12.
    Delp, S. L., & Loan, J. P. (1995). A graphics-based software system to develop and analyze models of musculoskeletal structures. Computers in Biology and Medicine, 25(1), 21–34.Google Scholar
  13. 13.
    Arnold, E. M., Samuel, R. W., Richard L. L., & Scott L. D, (2010). A model of the lower limb for analysis of human movement. Annals of Biomedical Engineering, 38(2), 269–279.Google Scholar
  14. 14.
    Delp, S. L., Loan, J. P., Melissa, G. H., Felix E. Z., Eric L. T., & Joseph M. R. (1990). An interactive graphics-based model of the lower extremity to study orthopaedic surgical procedures. IEEE Transactions on Biomedical Engineering, 37(8), 757–767.Google Scholar
  15. 15.
    Lenaerts, G., Ward, B., Frederik, G., Michiel, M., Arthur, S., Van der Perre, G., et al. (2009). Subject-specific hip geometry and hip joint centre location affects calculated contact forces at the hip during gait. Journal of Biomechanics, 42(9), 1246–1251.Google Scholar
  16. 16.
    Correa, T. A., Baker, R., & Pandy, M. G. (2011). Accuracy of generic musculoskeletal models in predicting the functional roles of muscles in human gait. Journal of Biomechanics, 44(11), 2096–2105.CrossRefGoogle Scholar
  17. 17.
    Cuypers, R., Tang, Z., Luther, W., & Pauli, J. (2008). Efficient and accurate femur reconstruction using model-based segmentation and superquadric shapes. Proceedings of the Fourth IASTED International Conference, 619(007), 99.Google Scholar
  18. 18.
    Brunner, G., Nambi, V., Yang, E., Kumar, A., Virani, S. S., Kougias, P., et al. (2011). Automatic quantification of muscle volumes in magnetic resonance imaging scans of the lower extremities. Magnetic Resonance Imaging, 29(8), 1065–1075.CrossRefGoogle Scholar
  19. 19.
    Schmid, J., Kim, J., & Magnenat-Thalmann, N. (2011). Extreme leg motion analysis of professional ballet dancers via MRI segmentation of multiple leg postures. International Journal of Computer Assisted Radiology and Surgery, 6(1), 47–57.CrossRefGoogle Scholar
  20. 20.
    Schmid, J., Sandholm, A., Chung, F., Thalmann, D., Delingette, H., & Magnenat-Thalmann, N. (2009). Musculoskeletal simulation model generation from MRI data sets and motion capture data. In Recent advances in the 3D physiological human (pp. 3–19). Berlin: Springer.Google Scholar
  21. 21.
    Teran, J., Sifakis, E., Blemker, S. S., Ng-Thow-Hing, V., Lau, C., & Fedkiw, R. (2005). Creating and simulating skeletal muscle from the visible human data set. IEEE Transactions on Visualization and Computer Graphics, 11(3), 317–328.Google Scholar
  22. 22.
    Nikravesh, PE. (1998). Computer-aided analysis of mechanical systems, Prentice-Hall Inc, NJ: Englewood Cliff.Google Scholar
  23. 23.
    Seireg, A., & Arvikar, R. J. (1973). A mathematical model for evaluation of forces in lower extremeties of the musculo-skeletal system. Journal of Biomechanics, 6(3), 313–326.CrossRefGoogle Scholar
  24. 24.
    Raikova, R. (1992). A general approach for modelling and mathematical investigation of the human upper limb. Journal of Biomechanics, 25(8), 857–867.CrossRefGoogle Scholar
  25. 25.
    Jensen, R. H., & Davy, D. T. (1975). An investigation of muscle lines of action about the hip: a centroid line approach vs the straight line approach. Journal of Biomechanics, 8(2), 103–110.Google Scholar
  26. 26.
    Blemker, S. S., & Delp, S. L. (2005). Three-dimensional representation of complex muscle architectures and geometries. Annals of Biomedical Engineering, 33(5), 661–673.Google Scholar
  27. 27.
    Van der Helm, F. C., Veeger, H. E., Pronk, G. M., Van der Woude, L. H., & Rozendal, R. H. (1992). Geometry parameters for musculoskeletal modelling of the shoulder system. Journal of Biomechanics, 25(2), 129–144.CrossRefGoogle Scholar
  28. 28.
    Arnold, A. S., Salinas, S., Asakawa, D. J., & Delp, S. L. (2000). Accuracy of muscle moment arms estimated from MRI-based musculoskeletal models of the lower extremity. Computer Aided Surgery, 5(2), 108–119.Google Scholar
  29. 29.
    Garner, B. A., & Pandy, M. G. (2000). The Obstacle-set method for representing muscle paths in musculoskeletal models. Computer Methods in Biomechanics and Biomedical Engineering, 3(1), 1–30. doi: 10.1080/10255840008915251.
  30. 30.
    Lieber, R. L., & Fridén, J. (2000). Functional and clinical significance of skeletal muscle architecture. Muscle and Nerve, 23(11), 1647–1666.CrossRefGoogle Scholar
  31. 31.
    Hill, A. V. (1938). The heat of shortening and the dynamic constants of muscle. Proceedings of the Royal Society, B126, 136–195.CrossRefGoogle Scholar
  32. 32.
    Zajac, F. E. (1989). Muscle and tendon: Properties, models, scaling, and application to biomechanics and motor control. Critical Reviews in Biomedical Engineering, 17(4), 359.Google Scholar
  33. 33.
    Blemker, S. S., Asakawa, D. S., Gold, G. E., & Delp, S. L. (2007). Image-based musculoskeletal modeling: Applications, advances, and future opportunities. Journal of Magnetic Resonance Imaging, 25(2), 441–451.Google Scholar
  34. 34.
    Veeger, D. H. (2011). “What if”: The use of biomechanical models for understanding and treating upper extremity musculoskeletal disorders. Manual Therapy, 16(1), 48–50.Google Scholar
  35. 35.
    Stewart, C., & Shortland, A. P. (2010). The biomechanics of pathological gait-from muscle to movement. Acta of Bioengineering and Biomechanics, 12(3), 3–12.Google Scholar
  36. 36.
    Anderson, A. E., Ellis, B. J., & Weiss, J. A. (2007). Verification, validation and sensitivity studies in computational biomechanics. Computer Methods in Biomechanics and Biomedical Engineering, 10(3), 171–184.Google Scholar
  37. 37.
    Leardini, A., Chiari, L., Croce, U. D., Cappozzo, A., et al. (2005). Human movement analysis using stereophotogrammetry. Part 3. Soft tissue artifact assessment and compensation. Gait and Posture, 21(2), 212.Google Scholar
  38. 38.
    Lu, T. W., & O’connor, J. J. (1999). Bone position estimation from skin marker coordinates using global optimisation with joint constraints. Journal of biomechanics, 32(2), 129–134.Google Scholar
  39. 39.
    Högfors, C., Peterson, B., Sigholm, G., & Herberts, P. (1991). Biomechanical model of the human shoulder joint–II. The shoulder rhythm. Journal of Biomechanics, 24(8), 699–709.CrossRefGoogle Scholar
  40. 40.
    Komistek, R. D., Kane, T. R., Mahfouz, M., Ochoa, J. A., & Dennis, D. A. (2005). Knee mechanics: A review of past and present techniques to determine in vivo loads. Journal of Biomechanics, 38, 215–228.CrossRefGoogle Scholar
  41. 41.
    Anderst, W., Zauel, R., Bishop, J., Demps, E., & Tashman, S. (2009). Validation of three-dimensional model-based tiobio-femoral tracking during running. Medical Engineering and Physics, 31, 10–16.CrossRefGoogle Scholar
  42. 42.
    Nester, C. J., et al. (2009). Lessons from dynamic cadaver and invasive bone pin studies: Do we know how the foot really moves during gait. Journal of Foot and Ankle Research, 2, 18.Google Scholar
  43. 43.
    Hurschler, C., Wülker, N., Windhagen, H., Hellmers, N., & Plumhoff, P. (2004). Evaluation of the lag sign tests for external rotator function of the shoulder. Journal of Shoulder and Elbow Surgery, 13(3), 298–304.CrossRefGoogle Scholar
  44. 44.
    Elias, J. J., Kirkpatrick, M. S., Saranathan, A., Mani, S., Smith, L. G., & Tanaka, M. J. (2011). Hamstrings loading contributes to lateral patellofemoral malalignment and elevated cartilage pressures: An in vitro study. Clinical Biomechanics, 26(8), 841–846.Google Scholar
  45. 45.
    Wünschel, M., Leichtle, U., Obloh, C., Wülker, N., & Müller, O. (2011). The effect of different quadriceps loading patterns on tibiofemoral joint kinematics and patellofemoral contact pressure during simulated partial weight-bearing knee flexion. Knee Surgery, Sports Traumatology, Arthroscopy, 19(7), 1099–1106.Google Scholar
  46. 46.
    Wülker, N., Hurschler, C., & Emmerich, J. (2003). In vitro simulation of stance phase gait part II: Simulated anterior tibial tendon dysfunction and potential compensation. Foot and Ankle International, 24, 623–629.Google Scholar
  47. 47.
    Wünschel, M., Leichtle, U., Lo, J., Wülker, N., & Müller, O. (2012). Differences in tibiofemoral kinematics between the unloaded robotic passive path and a weightbearing knee simulator. Orthopedic Reviews, 4(1), e2. doi: 10.4081/or.2012.e2.
  48. 48.
    Davoodi, Rahman, & Gerald, E. (2002). A software tool for faster development of complex models of musculoskeletal systems and sensorimotor controllers in simulinkTM. Journal of Applied Biomechanics, 18(4), 357–365.Google Scholar
  49. 49.
    Delp, S. L., Frank, C., Chand, T., & Darryl, G. (2007). OpenSim: Open-source software to create and analyze dynamic simulations of movement. IEEE Transactions on Biomedical Engineering, 54(11), 1940–1950.CrossRefGoogle Scholar
  50. 50.
    Mansouri, M., & Reinbolt, J. A. (2012). A platform for dynamic simulation and control of movement based on OpenSim and MATLAB. Journal of Biomechanics, 45(8), 1517–1521.Google Scholar
  51. 51.
    Higginson, J. S., Zajac, F. E., Neptune, R. R., Kautz, S. A., & Delp, S. L. (2006). Muscle contributions to support during gait in an individual with post-stroke hemiparesis. Journal of Biomechanics, 39(10), 1769–1777.CrossRefGoogle Scholar
  52. 52.
    Jonkers, I., Stewart, C., Desloovere, K., Molenaers, G., & Spaepen, A. (2006). Musculo-tendon length and lengthening velocity of rectus femoris in stiff knee gait. Gait and Posture, 23(2), 222–229.Google Scholar
  53. 53.
    Crabtree, C. A., & Jill, S. (2009). Modeling neuromuscular effects of ankle foot orthoses (AFOs) in computer simulations of gait. Gait and Posture, 29(1), 65–70.CrossRefGoogle Scholar
  54. 54.
    Nair, P. M., Rooney, K. L. Kautz, S. A. Behrman, A. L. et al. (2010). Stepping with an ankle foot orthosis re-examined: A mechanical perspective for clinical decision making. Clinical Biomechanics (Bristol, Avon), 25(6), 618.Google Scholar
  55. 55.
    Sherman, M. A., & Seth, A. (2011). Simbody: Multibody dynamics for biomedical research. Procedia IUTAM, 2, 241–261.CrossRefGoogle Scholar
  56. 56.
    Silverman, A. K., & Neptune, R. R. (2010). Individual muscle function in below Knee amputee walking. In Conference Proceedings of the Annual Meeting of the American Society, p. 166.Google Scholar
  57. 57.
    Fey, N. P., Klute, G. K., & Neptune, R. R. (2013). Altering prosthetic foot stiffness influences foot and muscle function during below-knee amputee walking: A modeling and simulation analysis. Journal of Biomechanics, 46(4), 637–644.Google Scholar
  58. 58.
    Worsley, P., Stokes, M., & Taylor, M. (2011). Predicted knee kinematics and kinetics during functional activities using motion capture and musculoskeletal modelling in healthy older people. Gait and Posture, 33(2), 268–273.Google Scholar
  59. 59.
    Michiel, O., Telfezr, S., Tørholm, S., Carbes, S., van Rhijn, L., Ross, M. et al. (2011). Generation of subject-specific, dynamic, multisegment ankle and foot models to improve orthotic design: A feasibility study. BMC Musculoskeletal Disorders, 12(1), 256.Google Scholar
  60. 60.
    Nolte, D., Andersen, M. S., Rasmussen, J., & Al-Munajjed, A. (2013). Development of a patient-specific musculoskeletal model of a healthy knee to analyze hard and soft tissue loading. In 21th Annual Symposium on Computational Methods in Orthoopeadic Biomechanics.Google Scholar
  61. 61.
    Alkjær, T., Wieland, M. R., Andersen, M. S., Simonsen, E. B., & John, R. (2012). Computational modeling of a forward lunge: Towards a better understanding of the function of the cruciate ligaments. Journal of Anatomy, 221(6), 590–597.Google Scholar
  62. 62.
    Ali, Nicholas, Michael Skipper Andersen, John Rasmussen, D Gordon E Robertson, and Gholamreza Rouhi. 2013. “The application of musculoskeletal modeling to investigate gender bias in non-contact ACL injury rate during single-leg landings”. Computer methods in biomechanics and biomedical engineering (ahead-of-print): 1–15.Google Scholar
  63. 63.
    Cao, E., Inoue, Y. Liu, T. & Shibata, K. (2012). Estimation of lower limb muscle forces during human sit-to-stand process with a rehabilitation training system. In 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), pp. 1016–1019.Google Scholar
  64. 64.
    Lemieux, P. O., Tétreault, P. Hagemeister, N. & Nuño, N. (2012). Influence of prosthetic humeral head size and medial offset on the mechanics of the shoulder with cuff tear arthropathy: A numerical study. Journal of Biomechanics, 46(3), 806–812.Google Scholar
  65. 65.
    Jackson, M., Sylvestre, É. Bleau, J. Allard, P & Begon, M. (2012). Estimating optimal shoulder immobilization postures following surgical repair of massive rotator cuff tears. Journal of Biomechanics46(1), 179–182.Google Scholar
  66. 66.
    Galibarov, P. E., Dendorfer, S., & Rasmussen, J. (2011). Two computational models of the lumbar spine: Comparison and validation. Long Beach, CA: ORS—Orthopaedic Research Society.Google Scholar
  67. 67.
    Han, K. S., Zander, T., Taylor, W. R., & Rohlmann, A. (2012). An enhanced and validated generic thoraco-lumbar spine model for prediction of muscle forces. Medical Engineering and Physics, 34(6), 709–716.Google Scholar
  68. 68.
    Ulrey, B. L., & Fathallah, F. A. (2012). Subject-specific, whole-body models of the stooped posture with a personal weight transfer device. Journal of Electromyography and Kinesiology.Google Scholar
  69. 69.
    Lundberg, H. J., Foucher, K. C., Andriacchi, T. P., & Wimmer, M. A. (2012). Direct comparison of measured and calculated total knee replacement force envelopes during walking in the presence of normal and abnormal gait patterns. Journal of Biomechanics, 45(6), 990–996.Google Scholar
  70. 70.
    Taddei, F., Martelli, S., Valente, G., Leardini, A., Benedetti, M, G., Manfrini, M., et al. (2012). Femoral loads during gait in a patient with massive skeletal reconstruction. Clinical Biomechanics, 27(3), 273–280.Google Scholar
  71. 71.
    Donnelly, C. J., & Lloyd, D. G. (2012). Optimizing whole-body kinematics to minimize valgus knee loading during sidestepping: Implications for ACL injury risk. Journal of Biomechanics, 45(8), 1491–1497.CrossRefGoogle Scholar
  72. 72.
    Crossley, K. M, Dorn, T. W. Ozturk, H., van den Noort, J., Schache, A. G., & Pandy, M. G. (2012). Altered hip muscle forces during gait in people with patellofemoral osteoarthritis. steoarthritis and Cartilage.Google Scholar
  73. 73.
    Mansouri, M., Clark, A. E., & Reinbolt, J. A. (2012). The use of a platform for dynamic simulation of movement: Application to balance recovery. Proceedings of the American Society of Biomechanics, Gainesville, FL. Aug. 2012 (Available at:
  74. 74.
    Branemark, R., Branemark, P. I., Rydevik, B., & Myers, R. R. (2001). Osseointegration in skeletal reconstruction and rehabilitation: A review. Journal of rehabilitation research and development, 38(2), 175–182.Google Scholar
  75. 75.
    Brånemark, P. I. (1983). Osseointegration and its experimental background. The Journal of prosthetic dentistry, 50(3), 399–410.CrossRefGoogle Scholar
  76. 76.
    Hagberg, K., Branemark, R., Guntorberg, B., et al. (2008). Osseointegrated trans-femoral amputation prostheses: Pro-spective results of general and condition-specific quality of life in 18 patients at 2-year follow-up. Prosthetics and Orthotics International, 32, 29–41.CrossRefGoogle Scholar
  77. 77.
    Grundei, H., Von Stein, T., Schulte-Bockhof, D., Kausch, C., Gollwitzer, H., & Gradinger, R. (2009). Die Endo-Exo-Femurprothese—Update eines Versorgungskonzeptes zur Rehabilitation von Oberschenkelamputierten. Orthopädie-Technik, 12, 143–149.Google Scholar
  78. 78.
    Kadaba, M. P., Ramakrishnan, H. K., & Wootten, M. E. (1990). Measurement of lower extremity kinematics during level walking. Journal of Orthopaedic Research?: official publication of the Orthopaedic Research Society, 8(3), 383–92. doi:10.1002/jor.1100080310.Google Scholar
  79. 79.
    Vicon Plug-in Gait Product Guide–Foundation Notes Revision 2.0 March 2010 For use with Plug-in Gait Version 2.0 in Vicon Nexus, 2010.Google Scholar
  80. 80.
    Tomaszewski, P. K., Verdonschot, N., Bulstra, S. K., & Verkerke, G. J. (2010). A comparative finite-element analysis of bone failure and load transfer of osseointegrated prostheses fixations. Annals of Biomedical Engineering, 38(7), 2418–2427.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  • Karelia Tecante
    • 1
    Email author
  • Frank Seehaus
    • 1
  • Bastian Welke
    • 1
  • Gavin Olender
    • 1
  • Michael Schwarze
    • 1
  • Sean Lynch
    • 1
  • Christoph Hurschler
    • 1
  1. 1.Laboratory for Biomechanics and Biomaterials (LBB) Orthopaedic DepartmentHannover Medical School (MHH)HannoverGermany

Personalised recommendations