Abstract
By following the common definition of forward-dynamics simulations, i.e. predicting movement based on (neural) muscle activity, this work describes, for the first time, a forward-dynamics simulation framework of a musculoskeletal system, in which all components are represented as continuous, three-dimensional, volumetric objects. Within this framework, the mechanical behaviour of the entire muscle–tendon complex is modelled as a nonlinear hyperelastic material undergoing finite deformations. The feasibility and the full potential of the proposed forward-dynamics simulation framework is demonstrated on a two-muscle, three-dimensional, continuum-mechanical model of the upper limb. The musculoskeletal model consists of three bones, i.e. humerus, ulna, and radius, an one-degree-of-freedom elbow joint, and an antagonistic muscle pair, i.e. the biceps and triceps brachii, and takes into consideration the contact between the skeletal muscles and the humerus. Numerical studies have shown that the proposed upper limb model is capable of predicting realistic moment arms and muscle forces for the entire range of activation and motion. Within the limitations of the model, the presented simulations provide, for the first time, insights into existing contact forces and their influence on the muscle fibre stretch. Based on the presented simulations, the overall change in fibre stretch is typically less than 3%, despite the fact that the contact forces reach up to 71% of the exerted muscle force. Movement-predicting simulations are achieved by minimising a nonlinear moment equilibrium equation. Based on the forward-dynamics simulation approach, an iterative solution procedures for position-driven (inverse dynamics) and force-driven scenarios have been proposed accordingly. Applying these methodologies to time-dependent scenarios demonstrates that the proposed methods can be linked to state-of-the-art control algorithms predicting time-dependent muscle activation levels based on principles of forward dynamics.
Similar content being viewed by others
Notes
An interactive computer program for Continuum Mechanics, Image analysis, Signal processing and System Identification (http://www.cmiss.org).
References
Alexander RM, Vernon A (1975) The dimensions of knee and ankle muscles and the forces they exert. J Human Mov Stud 1(1):115–123
Amis AA, Dowson D, Wright V (1980) Analysis of elbow forces due to high-speed forearm movements. J Biomech 13(10):825–831
An KN, Takahashi K, Harrigan TP, Chao EY (1984) Determination of muscle orientations and moment arms. J Biomech Eng 106(3):280–282
An KN, Kaufman KR, Chao EYS (1989) Physiological considerations of muscle force through the elbow joint. J Biomech 22(11):1249–1256
Anderson FC (1999) A dynamic optimization solution for a complete cycle of normal gait. PhD thesis, University of Texas at Austin
Anderson FC, Pandy MG (2001) Static and dynamic optimization solutions for gait are practically equivalent. J Biomech 34(2):153–161
Biodex Medical Systems I (2006) Biodex multi-joint system—PRO, Setup and operation manual. www.biodex.com
Blemker SS, Delp SL (2005) Three-dimensional representation of complex muscle architectures and geometries. Ann Biomed Eng 33(5):661–673
Blemker SS, Pinsky PM, Delp SL (2005) A 3d model of muscle reveals the causes of nonuniform strains in the biceps brachii. J Biomech 38:657–665
Böl M, Sturmat M, Weichert C, Kober C (2011) A new approach for the validation of skeletal muscle modelling using MRI data. Comput Mech 47(5):591–601
Bonet J, Wood RD (1997) Nonlinear continuum mechanics for finite element analysis. Cambridge University Press, Cambridge
Buchanan TS, Almdale DPJ, Lewis JL, Rymer WZ (1986) Characteristics of synergic relations during isometric contractions of human elbow muscles. J Neurophysiol 56(5):1225–41
Buchanan TS, Delp SL, Solbeck JA (1998) Muscular resistance to varus and valgus loads at the elbow. J Biomech Eng 120(5):634–639
Buchanan TS, Lloyd DG, Manal K, Besier TF (2004) Neuromusculoskeletal modeling: estimation of muscle forces and joint moments and movements from measurements of neural command. J Appl Biomech 20(4):367
Chi SW, Hodgson J, Chen JS, Edgerton VR, Shin DD, Roiz RA, Sinha S (2010) Finite element modeling reveals complex strain mechanics in the aponeuroses of contracting skeletal muscle. J Biomech 43(7):1243–1250
Chris BP, Andrew PJ, Hunter PJ (1997) Geometric modeling of the human torso using cubic hermite elements. Ann Biomed Eng 25:96–111
Christophy M, Faruk Senan NA, Lotz JC, O’Reilly OM (2011) A musculoskeletal model for the lumbar spine. Biomech Model Mechanobiol 11(1–2):19–34
Chung JH (2008) Modelling mammographic mechanics. PhD thesis, Auckland Bioengineering Institute, The University of Auckland, New Zealand
Crowninshield RD, Brand RA (1981) A physiologically based criterion of muscle force prediction in locomotion. J Biomech 14(11):793–801
Feldman AG (1986) Once more on the equilibrium-point hypothesis (\(\lambda \) model) for motor control. J Motor Behav 18(1):17–54
Fernandez JW, Hunter PJ (2005) An anatomically based patient-specific finite element model of patella articulation: towards a diagnostic tool. Biomech Model Mechanobiol 4(1):20–38
Fiorentino NM, Epstein FH, Blemker SS (2012) Activation and aponeurosis morphology affect in vivo muscle tissue strains near the myotendinous junction. J Biomech 45(4):647–652. doi:10.1016/j.jbiomech.2011.12.015
Garner BA, Pandy MG (2000) The obstacle-set method for representing muscle paths in musculoskeletal models. Comput Method Biomech Biomed Eng 3(1):1–30
Günther M, Ruder H (2003) Synthesis of two-dimensional human walking: a test of the \(\lambda \)-model. Biol Cybern 8:89–106
Günther M, Schmitt S, Wank V (2007) High-frequency oscillations as a consequence of neglected serial damping in Hill-type muscle models. Biol Cybern 97(1):63–79. doi:10.1007/s00422-007-0160-6
Günther M, Schmitt S, Wank V (2007) High-frequency oscillations as a consequence of neglected serial damping in hill-type muscle models. Biol Cybern 97(1):63–79
Haeufle D, Günther M, Bayer A, Schmitt S (2014) Hill-type muscle model with serial damping and eccentric force-velocity relation. J Biomech 47(6):1531–1536
Hatze H (1978) A general myocybernetic control model of skeletal muscle. Biol Cybern 28(3):143–157
Hawkins D, Bey M (1994) A comprehensive approach for studying muscle-tendon mechanics. J Biomech Eng 116(1):51–55
Heidlauf T, Röhrle O (2013) Modeling the chemoelectromechanical behavior of skeletal muscle using the parallel open-source software library OpenCMISS. Comput Math Methods Med 2013:1–14. doi:10.1155/2013/517287
Heidlauf T, Röhrle O (2014) A multiscale chemo-electro-mechanical skeletal muscle model to analyze muscle contraction and force generation for different muscle fiber arrangements. Front Physiol 5(498):1–14. doi:10.3389/fphys.2014.00498
Heidlauf T, Negro F, Farina D, Röhrle O (2013) An integrated model of the neuromuscular system. In: 2013 6th International IEEE/EMBS conference on neural engineering (NER), IEEE, pp 227–230. doi:10.1109/NER.2013.6695913
Hof AL, Van Den Berg JW (1977) Linearity between the weighted sum of the EMGs of the human triceps surae and the total torque. J Biomech 10(9):529–539
Holzapfel GA (2000) Nonlinear solid mechanics: a continuum approach for engineering. Wiley, New York
Houdijk H, Bobbert MF, de Haan A (2006) Evaluation of a Hill based muscle model for the energy cost and efficiency of muscular contraction. J Biomech 39(3):536–543. doi:10.1016/j.jbiomech.2004.11.033
Kistemaker DA, Van Soest AJ, Bobbert MF (2006) Is equilibrium point control feasible for fast goal-directed single-joint movements? J Neurophysiol 95(5):2898–2912. doi:10.1152/jn.00983.2005
Laursen TA (2002) Computational contact and impact mechanics: fundamentals of modeling interfacial phenomena in nonlinear finite element analysis. Springer Science & Business Media, New York
Lee SH, Sifakis E, Terzopoulos D (2009) Comprehensive biomechanical modeling and simulation of the upper body. ACM Trans Graph 28(4):99
Lemos RR, Rokne J, Baranoski GVG, Kawakami Y, Kurihara T (2005) Modeling and simulating the deformation of human skeletal muscle based on anatomy and physiology. Comput Anim Virtual Worlds 16:319–330
Lloyd DG, Besier TF (2003) An emg-driven musculoskeletal model for estimation of the human knee joint moments across varied tasks. J Biomech 36:765–776
Lorussi F, Galatolo S, Caudai C, Tognetti A, De Rossi D (2006) Compliance control and feldman’s muscle model. In: The first IEEE/RAS-EMBS international conference on biomedical robotics and biomechatronics, 2006. BioRob 2006, IEEE, pp 1194–1199
Manal K, Buchanan TS (2003) A one-parameter neural activation to muscle activation model: estimating isometric joint moments from electromyograms. J Biomech 36(8):1197–1202. doi:10.1016/S0021-9290(03)00152-0
Markert B, Ehlers W, Karajan N (2005) A general polyconvex strain-energy function for fiber-reinforced materials. PAMM 5(1):245–246
Millard M, Uchida T, Seth A, Delp SL (2013) Flexing computational muscle: modeling and simulation of musculotendon dynamics. J Biomech Eng 135(2):021,005–021,011
Mooney M (1940) A theory of large elastic deformation. J Appl Phys 11(9):582–592
Mordhorst M, Heidlauf T, Röhrle O (2015) Predicting electromyographic signals under realistic conditions using a multiscale chemo-electro-mechanical finite element model. Interface Focus 5(2): doi:10.1098/rsfs.2014.0076
Mörl F, Siebert T, Schmitt S, Blickhan R, Günther M (2012) Electro-mechanical delay in Hill-type muscle models. J Mech Med Biol 12(5):85–102. doi:10.1142/S0219519412500856
Morrison JB (1970) The mechanics of the knee joint in relation to normal walking. J Biomech 3(1):51–61
Murray WM, Delp SL, Buchanan TS (1995) Variation of muscle moment arms with elbow and forearm position. J Biomech 28(5):513–525
Murray WM, Buchanan TS, Delp SL (2000) The isometric functional capacity of muscles that cross the elbow. J Biomech 33(8):943–952. doi:10.1016/S0021-9290(00)00051-8
Oomens CWJ, Maenhout M, van Oijen CH, Drost MR, Baaijens FP (2003) Finite element modelling of contracting skeletal muscle. Philos Trans R Soc B 358:1453–1460
Pandy MG, Zajac FE, Sim E, Levine WS (1990) An optimal control model for maximum-height human jumping. J Biomech 23(12):1185–1198
Rivlin RS (1948) Large elastic deformations of isotropic materials. IV. Further developments of the general theory. Philos Trans R Soc Lond Ser A Math Phys Sci 241(835):379–397
Röhrle O (2010) Simulating the electro-mechanical behavior of skeletal muscles. IEEE Comput Sci Eng 12(6):48–58. doi:10.1109/MCSE.2010.30
Röhrle O, Pullan AJ (2007) Three-dimensional finite element modelling of muscle forces during mastication. J Biomech 40(15):3363–3372
Röhrle O, Davidson JB, Pullan AJ (2008) Bridging scales: a three-dimensional electromechanical finite element model of skeletal muscle. J Sci Comput 30:2883–2904
Röhrle O, Davidson JB, Pullan AJ (2012) A physiologically based, multi-scale model of skeletal muscle structure and function. Front Physiol 3:1–14. doi:10.3389/fphys.2012.00358
Röhrle O, Sprenger M, Ramasamy E, Heidlauf T (2013) Multiscale skeletal muscle modeling: from cellular level to a multi-segment skeletal muscle model of the upper limb. Springer, Netherlands, pp 103–116. doi:10.1007/978-94-007-5464-5_8
Rupp TK, Ehlers W, Karajan N, Günther M, Schmitt S (2015) A forward dynamics simulation of human lumbar spine flexion predicting the load sharing of intervertebral discs, ligaments, and musclesT. K. Rupp, W. Ehlers, N. Karajan, M. Günther & S. Schmitt. Biomech Model Mechanobiol 14(5):1081–1105
Schipplein O, Andriacchi TP (1991) Interaction between active and passive knee stabilizers during level walking. J Orthop Res 9(1):113–119
Seireg A, Arvikar R (1975) The prediction of muscular load sharing and joint forces in the lower extremities during walking. J Biomech 8(2):89–102. doi:10.1016/0021-9290(75)90089-5
Seireg A, Arvikar RJ (1973) A mathematical model for evaluation of forces in lower extremeties of the musculo-skeletal system. J Biomech 6(3):313–326
Sharafi B, Blemker SS (2010) A micromechanical model of skeletal muscle to explore the effects of fiber and fascicle geometry. J Biomech 43(16):3207–3213
Sharafi B, Ames EG, Holmes JW, Blemker SS (2011) Strains at the myotendinous junction predicted by a micromechanical model. J Biomech 44(16):2795–2801
Siebert T, Rode C, Herzog W, Till O, Blickhan R (2008) Nonlinearities make a difference: comparison of two common Hill-type models with real muscle. Biol Cybern 98(2):133–143. doi:10.1007/s00422-007-0197-6
Siebert T, Till O, Stutzig N, Günther M, Blickhan R (2014) Muscle force depends on the amount of transversal muscle loading. J Biomech 47(8):1822–1828
Spencer A (1972) Deformations of fibre-reinforced materials. Oxford science research papers. Clarendon Press, Oxford
Spencer AJM (1971) Theory of invariants. Continuum Phys 1(Part III):239–352
Spitzer V, Ackerman MJ, Scherzinger AL, Whitlock D (1996) The visible human male: a technical report. J Am Med Inform Assoc 3:118–130
Van Soest AJ, Bobbert MF (1993) The contribution of muscle properties in the control of explosive movements. Biol Cybern 69(3):195–204
Weiss JA, Gardiner JC (2001) Computational modeling of ligament mechanics. Crit Rev Biomed Eng 29(3):303–371
Winters JM (1990) Hill-based muscle models: a systems engineering perspective. Springer, Berlin, pp 69–93
Wriggers P (2002) Computational contact mechanic. Wiley, New York
Wu T, Hung APL, Hunter P, Mithraratne K (2013) Modelling facial expressions: a framework for simulating nonlinear soft tissue deformations using embedded 3d muscles. Finite Elem Anal Des 76:63–70
Zajac FE (1989) Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Critical Rev Biomed Eng 17(4):359–411
Zheng Y, Mak AFT, Lue B (1999) Objective assessment of limb tissue elasticity: development of a manual indentation procedure. J Rehabil Res Dev 36(2):71–85
Acknowledgments
The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007–2013)/ERC Grant Agreement No. 306757 (LEAD).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors have no conflict of interest.
Rights and permissions
About this article
Cite this article
Röhrle, O., Sprenger, M. & Schmitt, S. A two-muscle, continuum-mechanical forward simulation of the upper limb. Biomech Model Mechanobiol 16, 743–762 (2017). https://doi.org/10.1007/s10237-016-0850-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10237-016-0850-x