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Biomechanics of Human Iliopsoas and Functionally Related Muscles

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The Evolved Athlete: A Guide for Elite Sport Enhancement

Abstract

One of the causes of pain in the lumbosacral spine is the overexertion of the following muscles: quadratus lumborum, rectus abdominis, erector spinae group, gluteus maximus et medius, and piriformis.

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Notes

  1. 1.

    Lagrangian \(L\left( q,\dot{q}\right) \) is called regular when the symmetric matrix \([\partial ^{2}L/\partial \dot{q}^{i}\partial \dot{q} ^{j}],~(i,j=1,\ldots ,n)\) is everywhere nonsingular.

  2. 2.

    Recall that Kalman filter was the algorithm that was steering the Apollo 11 spaceflight in July 1969, that took Neil Armstrong and Buzz Aldrin to the moon and brought them back home.

  3. 3.

    A product of two Gaussians is another Gaussian; a Fourier transform of a Gaussian is the same Gaussian.

  4. 4.

    This Gaussian restriction is a characteristic of Kalman filtering; giving up of this restriction leads to a family of particle filters , in which the result of measurements are represented as a weighted sum of Dirac-delta functions.

  5. 5.

    In general, someone’s belief in an event or statement A will depend on their body of knowledge K. Formally, this is a belief measure, or a degree-of-belief: p(A|K), where \((\cdot |\cdot )\) means ‘given’. When K remains constant, we simply write p(A) instead of p(A|K); however, any statement about p(A) is always conditioned on a context K.

    The conditional probability p(A|B) of an event A given another event B is the probability that the event A will happen given that the event B has already occurred. Also, when we have a joint event A and B, we have a joint probability : p (AB), where \((\cdot ,\cdot )\) means ‘and’, \(\wedge \), or ‘joint’. Conditional probabilities can be defined via joint probabilities and vice versa: \( p(A|B)=p(A,B)/p(B) \), which implies: \(p(A,B)=p(A|B)p(B)\).

  6. 6.

    The general Bayesian filter attempts to recover the information about the current system state \(x_{t}\) (at time t) based on the available measurements \(y_{1:t}\) (at previous times \(1,\ldots ,t\)). Formally, the Bayesian filter includes the dynamics-given time-update recursion for calculating the Prior PDF:

    $$\begin{aligned} \overset{\mathrm {Prior}}{p(x_{t}|y_{1:t-1})}=\int _{\mathbb {R}^{n}}\overset{ \mathrm {Dynamics}}{p(x_{t}|x_{t-1})}\overset{\mathrm {Previous\,Prior}}{ \,p(x_{t-1}|y_{1:t-1})}dx_{t-1}\,, \end{aligned}$$

    and the measurement-update recursion for calculating the Posterior (i.e., the filter PDF) using the Bayes rule:

    $$\begin{aligned} \overset{\mathrm {Posterior}}{p(x_{t}|y_{1:t})}=\,\overset{\mathrm {Prior}}{ p(x_{t}|y_{1:t-1})\,\,}\overset{\mathrm {Likelihood}}{p(y_{t}|x_{t})} \,/\,Z_{t}, \end{aligned}$$

    where \(Z_{t}\) is the normalizing constant (i.e., the partition function) defined by:

    $$\begin{aligned} Z_{t}=\int _{\mathbb {R}^{n}}p(x_{t}|y_{1:t-1})p(y_{t}|x_{t})dx_{t}\,. \end{aligned}$$
  7. 7.

    The exponential map is a map from the orthogonal rotational Lie group \( G=SO(3)\) to its Lie algebra \(\mathfrak {g}=\mathfrak {so}(3)\), that is, \(\exp :SO(3)\rightarrow \mathfrak {so}(3)\). It is sometimes called the Lie functor [40].

  8. 8.

    The logarithm map is a map from the Lie algebra \(\mathfrak {g}=\mathfrak {so} (3)\) to its Lie group \(G=SO(3)\), \(\log =\exp ^{-1}:\mathfrak {so} (3)\rightarrow SO(3)\). It is sometimes called the inverse Lie functor [40].

  9. 9.

    A slightly modified form of the basic BGC-maneuver is also an essential part of the pole-vault maneuver.

  10. 10.

    The pole vault was introduced as a full medal Olympic event in 1896 Olympic Games.

  11. 11.

    We remark that there are no restrictions on the material the pole is made from (currently it is either carbon-fibre or fibreglass) or the length of the pole.

References

  1. Anderson, F.C., Arnold, A.S., Pandy, M.G., Goldberg, S.R., Delp, S.L.: Simulation of Walking, Chapter 12 in Find an Expert. The University of Melbourne, Melbourne Research (2015)

    Google Scholar 

  2. Ait-Haddou, R., Binding, P., Herzog, W.: Theoretical considerations on cocontraction of sets of agonistic and antagonistic muscles. J. Biomech. 33(9), 1105–1111 (2000)

    Article  Google Scholar 

  3. Abraham, R., Marsden, J.: Foundations of Mechanics. Benjamin, Reading (1978)

    Google Scholar 

  4. Anderson, F.C., Pandy, M.G.: Dynamic Optimization of Human Walking. J. Biomech. Eng. 123, 381–390 (2001)

    Article  Google Scholar 

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

    Article  Google Scholar 

  6. Arampatzis, A., Schade, F., Bruggemann, G.P.: Effect of the pole-human body interaction on pole-vaulting performance. J. Biomech. 37, 1353–1360 (2004)

    Article  Google Scholar 

  7. Anderson, F.C., Ziegler, J.M., Pandy, M.G., Whalen, R.T.: Application of High-Performance Computing to Numerical Simulation of Human Movement. ASME J. Biomech. Eng. 117, 155–157 (1995)

    Article  Google Scholar 

  8. Alexander, F.H.: The theory of rowing. In: Proceedings of the University of Durham Philosophical Society, pp. 160–179 (1925)

    Google Scholar 

  9. Cabrera, D., Ruina, A., Kleshnev, V.: A simple 1\(^+\) dimensional model of rowing mimics observed forces and motions. Hum. Mov. Sci. 25, 192–220 (2006)

    Article  Google Scholar 

  10. Armbrust, W.: Energy conservation in pole vaulting. Track Tech. 125, 3991–3994 (1993)

    Google Scholar 

  11. Bogert, A.J., Blana, D., Heinrich, D.: Implicit methods for efficient musculoskeletal simulation and optimal control. Proc. IUTAM 2, 297–316 (2011)

    Article  Google Scholar 

  12. Braff, T., Dapena, J.: A two-dimensional simulation method for the Prediction of Movements in pole Vaulting. In: Jonsson, B. (ed.) Int. Ser. Biomech. vol. 5, pp. 458–463. Human Kinetics, Champaign, IL (1985)

    Google Scholar 

  13. Bloesch, M., Hutter, M., Hoepflinger, M., et al.: State estimation for legged robots—consistent fusion of leg kinematics and IMU. In: Proc. Robotics: Sci. Sys., pp. 12345. Sydney, AU

    Google Scholar 

  14. Bernado, J.M., Smith, A.F.M.: Bayesian Theory. Wiley, New York (1994)

    Book  Google Scholar 

  15. Bays, P.M., Wolpert, D.M.: Computational principles of sensorimotor control that minimize uncertainty and variability. J. Physiol. 578(2), 387–396 (2007)

    Article  Google Scholar 

  16. Bauer, W.L.: Swinging as a way of increasing the mechanical energy in gymnastic maneuvers. In: Matsui, H., Kobayashi, K. (eds.) Biomechanics VIII-B, pp. 801–806. Human Kinetics, Champaign, IL (1983)

    Google Scholar 

  17. Chaffin, D.B., Andersson, G.B.J., Martin, B.J.: Occupational Biomechanics, 3rd edn. Wiley-Interscience, New York (1999)

    Google Scholar 

  18. Chumanov, E.S., Heiderscheit, B.C., Thelen, D.G.: The effect of speed and influence of individual muscles on hamstring mechanics during the swing phase of sprinting. J. Biomech. 40(16), 3555–62 (2007)

    Article  Google Scholar 

  19. Cavanga, G.A.: Force Platforms as Ergometers. J. Appl. Physiol. 39, 174 (1975)

    Google Scholar 

  20. 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 

  21. Dickinson, M.H., Farley, C.T., Full, R.J., et al.: How Animals Move: an Integrative View. Science 288, 100 (2000)

    Article  Google Scholar 

  22. 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, 757–767 (1990)

    Article  Google Scholar 

  23. Ekevad, M., Lundberg, B.: Simulation of “smart” pole vaulting. J. Biomech. 28, 1079–1090 (1995)

    Article  Google Scholar 

  24. Ekevad, M., Lundberg, B.: Influence of pole length and stiffness on the energy conversion in pole-vaulting. J. Biomech. 30, 259–264 (1997)

    Article  Google Scholar 

  25. Gibson, W., Arendt-Nielsen, L., Graven-Nielsen, T.: Delayed onset muscle soreness at tendon-bone junction and muscle tissue is associated with facilitated referred pain. Exp. Brain. Res. 174(2), 351–360 (2006)

    Article  Google Scholar 

  26. Gibson, W., Arendt-Nielsen, L., Taguchi, T., et al.: Increased pain from muscle fascia following eccentric exercise: animal and human findings. Exp. Brain Res. 194(2), 299–308 (2009)

    Article  Google Scholar 

  27. Giat, Y., Mizrahi, J., Levy, M.: A musculotendon model of the fatigue profiles of paralyzed quadriceps muscle under fes. IEEE Trans. Biomed. Eng. 40(7), 664–674 (1993)

    Article  Google Scholar 

  28. Goldstein, H.: Classical Mechanics. Addison-Wesley, Boston, MA (1980)

    MATH  Google Scholar 

  29. He, J., Levine, W.S., Loeb, G.E.: Feedback gains for correcting small perturbations to standing posture. IEEE Trans. Autom. Control 36, 322–32 (1991)

    Article  MATH  Google Scholar 

  30. Hamner, S.R., Seth, A., Delp, S.L.: Muscle contributions to propulsion and support during running. J. Biomech. 43, 2709–16 (2010)

    Article  Google Scholar 

  31. Herzog, W.: Muscle. In: Nigg, B.M., Herzog, W. (eds.) Biomechanics of the Musculoskeletal System. 2nd edn., pp. 148–88. Wiley, New York (1999)

    Google Scholar 

  32. Hill, A.V.: The heat of shortening and the dynamic constants of muscle. Proc. R. Soc. B76, 136–195 (1938)

    Article  Google Scholar 

  33. Hill, A.V.: The dynamic constants of human muscle. Proc. R. Soc. B128, 263–274 (1940)

    Article  Google Scholar 

  34. Hill, A.V.: The series elastic component of muscles. Proc. R. Soc. B137, 273–280 (1950)

    Article  Google Scholar 

  35. Hill, A.V.: First and Last Experiments in Muscle Mechanics. Cambridge University Press, Cambridge (1970)

    Google Scholar 

  36. Huxley, A.F.: Muscle structure and theories of contraction. Progr. Biophys. Chem. 7, 255–328 (1957)

    Google Scholar 

  37. Ivancevic, T., Greenberg, H., Greenberg, R.: Enhancing Performance and Reducing Stress in Sports: Technological Advances, vol. 24. Springer Series: Cognitive Systems Monographs, Berlin (2015)

    Google Scholar 

  38. Ivancevic, V., Ivancevic, T.: Human-Like Biomechanics. Springer, New York (2006)

    Google Scholar 

  39. Ivancevic, V., Ivancevic, T.: Natural Biodynamics. World Scientific Press, Singapore (2006)

    Google Scholar 

  40. Ivancevic, V., Ivancevic, T.: Geometrical Dynamics of Complex Systems. Springer, New York (2006)

    Google Scholar 

  41. Ishii, H., Yanagiya, T., Naito, H., Katamoto, S., Maruyama, T.: Numerical study of ball behavior in side-foot soccer kick based on impact dynamic theory. J. Biomech. 42, 2712–20 (2009)

    Article  Google Scholar 

  42. Kalman, R.E.: A new approach to linear filtering and prediction problems. J. Basic Eng. 82(1), 35–45 (1960)

    Article  Google Scholar 

  43. Khalil, W.: Modeling and control of manipulators. Ecole Central de Nantes, Nantes (2009–2010)

    Google Scholar 

  44. Kokshenev, V.B.: Dynamics of Human Walking at Steady Speeds. Phys. Rev. Let. 93(20), 208101–1 (2004)

    Article  Google Scholar 

  45. Liu, J., Brown, R., Yue, G.: A dynamical model of muscle activation, fatigue, and recovery. Biophys. J. 82(5), 2344–2359 (2002)

    Article  Google Scholar 

  46. Landau, L.D., Lifshitz, E.M.: Mechanics. Pergamon Press, Oxford, UK (1976)

    MATH  Google Scholar 

  47. Linthorne, N.P.: Energy loss in the pole vault take-off and the advantage of the flexible pole. Sports Eng. 3, 205–218 (2000)

    Article  Google Scholar 

  48. Linthorne, N.: The Fiberglass Pole. In: Jarver, J. (ed.) The Jumps. Tafnews Press, Los Altos (1994)

    Google Scholar 

  49. Morlier, J., Cid, M.: Three-dimensional analysis of the angular momentum of a pole-vaulter. J. Biomech. 29, 1085–1090 (1996)

    Article  Google Scholar 

  50. Ma, L., Chablat, D., Bennis, F., Zhang, W.: A new simple dynamic muscle fatigue model and its validation. Int. J. Indust. Erg. 39(1), 211–220 (2009)

    Article  Google Scholar 

  51. Ma, R., Chablat, D., Bennis, F., Ma, L.: Human Muscle Fatigue Model in Dynamic Motions. In: Lenarcic, J., Husty, M. (eds.) Latest Advances in Robot Kinematics, pp. 349-356. Springer, Dordrecht, NL (2012)

    Google Scholar 

  52. Menegaldo, L.L., Fleury, A.T., Weber, H.I.: A ‘cheap’ optimal control approach to estimate muscle forces in musculoskeletal systems. J. Biomech. 39, 1787–1795 (2006)

    Article  Google Scholar 

  53. Morlier, J., Mesnard, M.: Influence of the moment exerted by the athlete on the pole in pole-vaulting performance. J. Biomech. 40, 2261–2267 (2007)

    Article  Google Scholar 

  54. Marsden, J.E., Ratiu, T.S.: Introduction to Mechanics and Symmetry: A Basic Exposition of Classical Mechanical Systems, 2nd edn. Springer, New York (1999)

    Book  MATH  Google Scholar 

  55. Haeufle, D.F.B., Günther, M., Bayer, A., Schmitt, S.: Hill-type muscle model with serial damping and eccentric force-velocity relation. J. Biomech. 47, 1531–1536 (2014)

    Article  Google Scholar 

  56. Molloy, M., Salazar-Torres, J., Kerr, C., McDowell, B.C., Cosgrove, A.P.: The effects of industry standard averaging and filtering techniques in kinematic gait analysis. Gait Posture 28(4), 559–62 (2008)

    Article  Google Scholar 

  57. Marsden, J.E., West, M.: Discrete mechanics and variational integrators. Acta Num. 10, 357–514 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  58. Ma, L., Zhang, W., Hu, B., et al.: Determination of subject-specific muscle fatigue rates under static fatiguing operations. Ergonomics 56(12), 1889–1900 (2013)

    Article  Google Scholar 

  59. Sakka, S., Chablat, D., Ma, R., et al.: Predictive model of the human muscle fatigue: application to repetitive push-pull tasks with light external load. Int. J. Human Factors Mod. Sim., Indersci. 5(1), 81–97 (2015)

    Google Scholar 

  60. McWatt, B.: The mechanics of take off in jumping events. In: Jarver, J. (ed) The Jumps. Tafnews Press, Los Altos (1994)

    Google Scholar 

  61. Michele, A.A.: Iliopsoas; development of anomalies in man. Thomas Publishing, Springfield, Ill (1962)

    Google Scholar 

  62. Neptune, R.R., Clark, D.J., Kautz, S.A.: Modular control of human walking: A simulation study. J. Biomech. 42, 1282–1287 (2009)

    Article  Google Scholar 

  63. Ober-Bloebaum, S., Junge, O., Marsden, J.E.: Discrete Mechanics and Optimal Control: an Analysis (2008). arXiv:0810.1386 [math.OC]

  64. Park, S., Han, Y., Hahn, H.: Balance control of a biped robot using camera image of reference object. Int. J. Con. Aut. Sys. 7(1), 75–84 (2009)

    Article  Google Scholar 

  65. Pandy, M.G., Zajac, F.E., Sim, E., Levine, W.S.: An optimal control model for maximum-height human jumping. J. Biomech. 23, 1185–1198 (1990)

    Article  Google Scholar 

  66. Rotella, N., Bloesch, M., Righetti, L., Schaal, S.: State Estimation for a Humanoid Robot. iN: IEEE RSJ Int. Con. IntelL. Rob. SysT., pp. 952–958 (2014)

    Google Scholar 

  67. Roberts, J., Marsh, R.L., Weyand, P.G., Taylor, C.R.: Muscular Force in Running Turkeys: The Economy of Minimizing Work. Science 275, 1113 (1997)

    Article  Google Scholar 

  68. Ralston, H.J.: Energetics of Human Walking. In: Herman, R.M., et al. (eds.) Neural Control of Locomotion, pp. 77–98. Plenum Press, New York (1976)

    Google Scholar 

  69. Schade, F., Arampatzis, A., Bruggemann, G.P.: Reproducibility of energy parameters in the pole vault. J. Biomech. 39, 146–147 (2006)

    Article  Google Scholar 

  70. Slater, H., Arendt-Nielsen, L., Wright, A., Graven-Nielsen, T.: Sensory and motor e V ects of experimental muscle pain in patients with lateral epicondylalgia and controls with delayed onset muscle soreness. Pain 114, 118–130 (2005)

    Article  Google Scholar 

  71. Thelen, D.G., Chumanov, E.S., Best, T.M., Swanson, S.C., Heiderscheit, B.C.: Simulation of biceps femoris musculotendon mechanics during the swing phase of sprinting. Med. Sci. Sports. Exerc. 37(11), 1931–8 (2005)

    Article  Google Scholar 

  72. Trawny, N., Roumeliotis, S.I.: Indirect Kalman filter for 3D attitude estimation. Univ. Minnesota, Dept. Comp. Sci. & Eng., Tech. Rep. 2005-002 (2005)

    Google Scholar 

  73. Vaslin, P., Couetard, Y., Cid, M.: Three dimensional dynamic analysis of the pole vault. J. Biomech. 27(6), 694 (1994)

    Article  Google Scholar 

  74. Willems, P.A., Cavanga, G.A., Heglund, N.C.: External, Internal and Total Work in Human Locomotion. J. Exp. Biol. 198, 379 (1995)

    Google Scholar 

  75. Wexler, A.S., Ding, J., Binder-Macleod, S.A.: A mathematical model that predicts skeletal muscle force. IEEE Trans. Biomed. Eng. 44(5), 337–348 (1997)

    Article  Google Scholar 

  76. Wikipedia: Runge-Kutta methods (2015)

    Google Scholar 

  77. Wikipedia: Recursive Bayesian estimation (2015)

    Google Scholar 

  78. Wikipedia: Pole vault (2015)

    Google Scholar 

  79. Yeadon, M.R., Hiley, M.J.: The mechanics of the backward giant circle on the high bar. Hum. Mov. Sci. 19, 153–173 (2000)

    Article  Google Scholar 

  80. Zhang, J., Lockhart, T.E., Soangra, R.: Classifying Lower Extremity Muscle Fatigue during Walking using Machine Learning and Inertial Sensors. Ann. Biomed. Eng. 42(3), 600–612 (2014)

    Article  Google Scholar 

  81. Zajac, F.E.: Muscle and tendon: Properties, models, scaling, and application to biomechanics and motor control. Crit. Rev. Biomed. Eng. 17, 359–411 (1989)

    Google Scholar 

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Ivancevic, T. et al. (2017). Biomechanics of Human Iliopsoas and Functionally Related Muscles. In: The Evolved Athlete: A Guide for Elite Sport Enhancement. Cognitive Systems Monographs, vol 32. Springer, Cham. https://doi.org/10.1007/978-3-319-57928-3_4

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