×

Minimal formulation of joint motion for biomechanisms. (English) Zbl 1206.92005

Summary: Biomechanical systems share many properties with mechanically engineered systems, and researchers have successfully employed mechanical engineering simulation software to investigate the mechanical behavior of diverse biological mechanisms, ranging from biomolecules to human joints. Unlike their man-made counterparts, however, biomechanisms rarely exhibit the simple, uncoupled, pure-axial motion that is engineered into mechanical joints such as sliders, pins, and ball-and-socket joints. Current mechanical modeling software based on internal-coordinate multibody dynamics can formulate engineered joints directly in minimal coordinates, but requires additional coordinates restricted by constraints to model more complex motions. This approach can be inefficient, inaccurate, and difficult for biomechanists to customize. Since complex motion is the rule rather than the exception in biomechanisms, the benefits of minimal coordinate modeling are not fully realized in biomedical research.
We introduce a practical implementation for empirically-defined internal-coordinate joints, which we call “mobilizers”. A mobilizer encapsulates the observations, measurement frame, and modeling requirements into a hinge specification of the permissible-motion manifold for a minimal set of internal coordinates. Mobilizers support nonlinear mappings that are mathematically equivalent to constraint manifolds but have the advantages of fewer coordinates, no constraints, and exact representation of the biomechanical motion-space, the benefits long enjoyed for internal-coordinate models of mechanical joints. Hinge matrices within the mobilizer are easily specified by user-supplied functions, and provide a direct means of mapping permissible motion derived from empirical data. We present computational results showing substantial performance and accuracy gains for mobilizers versus equivalent joints implemented with constraints. Examples of mobilizers for joints from human biomechanics and molecular dynamics are given. All methods and examples were implemented in Simbody\(^{\text{TM}}\), an open source multibody-dynamics solver available at https://Simtk.org.

MSC:

92C10 Biomechanics
92-08 Computational methods for problems pertaining to biology

References:

[1] Hurwitz, D.E., Ryals, A.R., Block, J.A., Sharma, L., Schnitzer, T.J., Andriacchi, T.P.: Knee pain and joint loading in subjects with osteoarthritis of the knee. J. Orthop. Res. 18(4), 572–579 (2000) · doi:10.1002/jor.1100180409
[2] Baliunas, A.J., Hurwitz, D.E., Ryals, A.B., Karrar, A., Case, J.P., Block, J.A., Andriacchi, T.P.: Increased knee joint loads during walking are present in subjects with knee osteoarthritis. Osteoarthr. Cartil. 10(7), 573–579 (2002) · doi:10.1053/joca.2002.0797
[3] Piazza, S.J., Delp, S.L.: Three-dimensional dynamic simulation of total knee replacement motion during a step-up task. J. Biomech. Eng. 123(6), 599–606 (2001) · doi:10.1115/1.1406950
[4] Isralewitz, B., Gao, M., Schulten, K.: Steered molecular dynamics and mechanical functions of proteins. Curr. Opin. Struct. Biol. 11(2), 224–230 (2001) · doi:10.1016/S0959-440X(00)00194-9
[5] Tang, S., Liao, J.-C., Dunn, A.R., Altman, R.B., Spudich, J.A., Schmidt, J.P.: Predicting allosteric communication in myosin via a pathway of conserved residues. J. Mol. Biol. 373(5), 1361–1373 (2007) · doi:10.1016/j.jmb.2007.08.059
[6] Sponer, J., Lankas, F. (eds.): Computational Studies of RNA and DNA. Springer, Berlin (2006)
[7] Kitano, H.: Systems biology: A brief overview. Science 295(5560), 1662–1664 (2002) · doi:10.1126/science.1069492
[8] Kuhlman, B., Dantas, G., Ireton, G.C., Varani, G., Stoddard, B.L., Baker, D.: Design of a novel globular protein fold with atomic-level accuracy. Science 302(5649), 1364–1368 (2003) · doi:10.1126/science.1089427
[9] Eich-Soellner, E., Fuhrer, C.: Numerical Methods in Multibody Dynamics. Tuebner, Leipzig (1998) · Zbl 0899.70001
[10] Kane, T.R., Likins, P.W., Levinson, D.A.: Spacecraft Dynamics. McGraw-Hill, New York (1983) · Zbl 0546.70015
[11] Jain, A.: Unified formulation of dynamics for serial rigid multibody systems. J. Guid. Control Dyn. 14, 531–542 (1991) · Zbl 0742.93057 · doi:10.2514/3.20672
[12] Brenan, K., Campbell, S., Petzold, L.R.: Numerical Solution of Initial-Value Problems in Differential-Algebraic Equations, 2nd edn. SIAM, Philadelphia (1987) · Zbl 0844.65058
[13] Baumgarte, J.: Stabilization of constraints and integrals of motion in dynamic systems. Comput. Methods Appl. Mech. Eng. 1, 1–16 (1972) · Zbl 0262.70017 · doi:10.1016/0045-7825(72)90018-7
[14] Eich, E.: Convergence results for a coordinate projection method applied to mechanical systems with algebraic constraints. SIAM J. Numer. Anal. 30(5), 1467–1482 (1993) · Zbl 0785.65079 · doi:10.1137/0730076
[15] Sobieszczanski-Sobieski, J., Haftka, R.T.: Multidisciplinary aerospace design optimization: Survey of recent developments. Struct. Multidiscip. Optim. 14(1), 1–23 (1997)
[16] Reinbolt, J., Schutte, J., Fregly, B., Koh, B., Haftka, R., George, A., Mitchell, K.: Determination of patient-specific multi-joint kinematic models through two-level optimization. J. Biomech. 38(3), 621–626 (2005) · doi:10.1016/j.jbiomech.2004.03.031
[17] Anderson, K.S., Hsu, Y.: Analytical fully-recursive sensitivity analysis for multibody dynamic chain systems. Multibody Syst. Dyn. 8(1), 1–27 (2002) · Zbl 1060.70010 · doi:10.1023/A:1015867515213
[18] Stryk, O.: Optimal control of multibody systems in minimal coordinates. ZAMM-Z. Angew. Math. Mech. 78, 1117–1120 (1998) · Zbl 0921.70020 · doi:10.1002/zamm.199807815124
[19] Lo, J., Metaxas, D.: Recursive dynamics and optimal control techniques for human motion planning. In: Computer Animation Proceedings, pp. 220–234. Geneva, Switzerland (1999)
[20] Neptune, R.R., Hull, M.L.: Evaluation of performance criteria for simulation of submaximal steady-state cycling using a forward dynamic model. J. Biomech. Eng. 120(3), 334–341 (1998) · doi:10.1115/1.2797999
[21] Anderson, F., Pandy, M.: A dynamic optimization solution for vertical jumping in three dimensions. Comput. Methods Biomech. Biomed. Eng. 2(3), 201–231 (1999) · doi:10.1080/10255849908907988
[22] Delp, S., Loan, J.: A computational framework for simulating and analyzing human and animal movement. Comput. Sci. Eng. 2(5), 46–55 (2000) · doi:10.1109/5992.877394
[23] McLean, S.G., Su, A., van den Bogert, A.J.: Development and validation of a 3-D model to predict knee joint loading during dynamic movement. J. Biomech. Eng. 125(6), 864–874 (2003) · doi:10.1115/1.1634282
[24] Brunger, A., Adams, P., Clore, G., DeLano, W., Gros, P., Grosse-Kunstleve, R., Jiang, J., Kuszewski, J., Nilges, M., Pannu, N.: Crystallography & NMR system: A new software suite for macromolecular structure determination. Acta Crystallogr. D Biol. Crystallogr. 54(5), 4449 (1998) · doi:10.1107/S0907444998003254
[25] Schwieters, C.D., Clore, G.M.: Internal coordinates for molecular dynamics and minimization in structure determination and refinement. J. Magn. Reson. 152(2), 288–302 (2001) · doi:10.1006/jmre.2001.2413
[26] Guntert, P., Mumenthaler, C., Wuthrich, K.: Torsion angle dynamics for NMR structure calculation with the new program Dyana. J. Mol. Biol. 273, 283 (1997) · doi:10.1006/jmbi.1997.1284
[27] Vaidehi, N., Jain, A., Goddard, W. III: Constant temperature constrained molecular dynamics: The Newton–Euler inverse mass operator method. J. Phys. Chem. 100(25), 10508–10517 (1996) · doi:10.1021/jp953043o
[28] Kalani, M.Y.S., Vaidehi, N., Hall, S.E., Trabanino, R.J., Freddolino, P.L., Kalani, M.A., Floriano, W.B., Kam, V.W.T., Goddard, W.A.: The predicted 3D structure of the human D2 dopamine receptor and the binding site and binding affinities for agonists and antagonists. Proc. Natl. Acad. Sci. USA 101(11), 3815–3820 (2004) · doi:10.1073/pnas.0400100101
[29] Tóth, G., Borics, A.: Flap opening mechanism of HIV-1 protease. J. Mol. Graph. 24(6), 465–474 (2006) · doi:10.1016/j.jmgm.2005.08.008
[30] Featherstone, R.: Robot Dynamics Algorithms. Kluwer, Amsterdam (1987)
[31] Rodriguez, G., Jain, A., Kreutz-Delgado, K.: Spatial operator algebra for multibody system dynamics. J. Astronaut. Sci. 44(1), 27–50 (1992)
[32] Anderson, K., Critchley, J.: Improved ’Order-N’ performance algorithm for the simulation of constrained multi-rigid-body dynamic systems. Multibody Syst. Dyn. 9(2), 185–212 (2003) · Zbl 1139.70304 · doi:10.1023/A:1022566107679
[33] Hollars, M.G., Rosenthal, D.E., Sherman, M.A.: SD/FAST User’s, Guide B.2 (1994)
[34] The Mathworks: Simmechanics 3 reference, October (2008)
[35] 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) · doi:10.1109/10.102791
[36] van der Helm, F.C.T.: Analysis of the kinematic and dynamic behavior of the shoulder mechanism. J. Biomech. 27(5), 527–550 (1994) · doi:10.1016/0021-9290(94)90064-7
[37] Krebs, W.G., Gerstein, M.: Survey and summary: The morph server: A standardized system for analyzing and visualizing macromolecular motions in a database framework. Nucleic Acids Res. 28(8), 1665–1675 (2000) · doi:10.1093/nar/28.8.1665
[38] Lee, S.-H., Terzopoulos, D.: Spline joints for multibody dynamics. ACM Trans. Graph. 27(3), 1–8 (2008) · doi:10.1145/1360612.1360621
[39] Jain, A., Vaidehi, N., Rodriguez, G.: A fast recursive algorithm for molecular dynamics simulation. J. Comput. Phys. 106(2), 258–268 (1993) · Zbl 0777.65038
[40] Kwatny, H.G., Blankenship, G.L.: Symbolic construction of models for multibody dynamics. IEEE Trans. Robot. Autom. 11(2), 271–281 (1995) · doi:10.1109/70.370509
[41] Mukherjee, R., Anderson, K.: Orthogonal complement based divide-and-conquer algorithm for constrained multibody systems. Nonlinear Dyn. 48(1), 199–215 (2007) · Zbl 1180.70006 · doi:10.1007/s11071-006-9083-3
[42] Featherstone, R.: The calculation of robot dynamics using articulated-body inertias. Int. J. Robot. Res. 2(1), 13–30 (1983) · doi:10.1177/027836498300200102
[43] Schmidt, J.P., Delp, S.L., Sherman, M.A., Taylor, C.A., Pande, V.S., Altman, R.B.: The Simbios National Center: Systems biology in motion. Proc. IEEE 96(8), 1266–1280 (2008) · doi:10.1109/JPROC.2008.925454
[44] Ryan, R.: Adams-multibody system analysis software. In: Schiehlen, W. (ed.) Multibody Systems Handbook. Springer, Berlin (1990)
[45] Fritzson, P.: Principles of Object-Oriented Modeling and Simulation with Modelica 2.1. IEEE, New York (2004)
[46] Featherstone, R.: Rigid Body Dynamics Algorithms, 2nd edn. Springer, Berlin (2008) · Zbl 1146.70002
[47] Gu, D., Chen, Y., Dai, K., Zhang, S., Yuan, J.: The shape of the acetabular cartilage surface: A geometric morphometric study using three-dimensional scanning. Med. Eng. Phys. 30(8), 1024–1031 (2008) · doi:10.1016/j.medengphy.2007.12.013
[48] De Sapio, V., Holzbaur, K., Khatib, O.: The control of kinematically constrained shoulder complexes: Physiological and humanoid examples. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 2952–2959, Orlando, FL. IEEE, New York (2006)
[49] Featherstone, R.: Plucker basis vectors. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 1892–1897, Orlando, FL. IEEE, New York (2006)
[50] Rodriguez, G.: Kalman filtering, smoothing, and recursive robot arm forward and inverse dynamics. IEEE J. Robot. Autom. 3(6), 624–639 (1987) · doi:10.1109/JRA.1987.1087147
[51] 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) · doi:10.1016/0021-9290(89)90179-6
[52] Wilson, D., Feikes, J., Zavatsky, A., O’Connor, J.: The components of passive knee movement are coupled to flexion angle. J. Biomech. 33(4), 465–473 (2000) · doi:10.1016/S0021-9290(99)00206-7
[53] Dennis, D.A., Komistek, R.D., Ho, W.A., Gabriel, S.M.: In vivo knee kinematics derived using an inverse perspective technique. Clin. Orthop. Relat. Res. 331, 107–117 (1996) · doi:10.1097/00003086-199610000-00015
[54] Thelen, D., Anderson, F.: Using computed muscle control to generate forward dynamic simulations of human walking from experimental data. J. Biomech. 39(6), 1107–1115 (2006) · doi:10.1016/j.jbiomech.2005.02.010
[55] 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) · doi:10.1109/TBME.2007.901024
[56] Liu, M., Anderson, F., Schwartz, M., Delp, S.: Muscle contributions to support and progression over a range of walking speeds. J. Biomech. 41(15), 3243–3252 (2008) · doi:10.1016/j.jbiomech.2008.07.031
[57] Leach, A.: Molecular Modelling: Principles and Applications. Longman, New York (1996)
[58] Sonnenschein, R.: An improved algorithm for molecular dynamics simulation of rigid molecules. J. Comput. Phys. 59(2), 347–350 (1985) · Zbl 0588.65002 · doi:10.1016/0021-9991(85)90151-2
[59] Chun, H.M., Padilla, C.E., Chin, D.N., Watanabe, M., Karlov, V.I., Alper, H.E., Soosaar, K., Blair, K.B., Becker, O.M., Caves, L.S.D., Nagle, R., Haney, D.N., Farmer, B.L.: MBO(n)D: A multibody method for long-time molecular dynamics simulations. J. Comput. Chem. 21(3), 159–184 (2000) · doi:10.1002/(SICI)1096-987X(200002)21:3<159::AID-JCC1>3.0.CO;2-J
[60] Flores, S.C., Keating, K.S., Painter, J., Morcos, F., Nguyen, K., Merritt, E.A., Kuhn, L.A., Gerstein, M.B.: Hingemaster: Normal mode hinge prediction approach and integration of complementary predictors. Proteins 73(2), 299–319 (2008) · doi:10.1002/prot.22060
[61] Humphrey, W., Dalke, A., Schulten, K.: VMD: Visual molecular dynamics. J. Mol. Graph. 14(1), 33–38 (1996) · doi:10.1016/0263-7855(96)00018-5
[62] Parker, D., Bryant, Z., Delp, S.L.: Coarse-grained structural modeling of molecular motors using multibody dynamics. Cell. Mol. Bioeng. 2(3), 366–374 (2009) · doi:10.1007/s12195-009-0084-4
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.