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Investigation of the effects of human body stability on joint angles’ prediction. (English) Zbl 1361.70012

Summary: Loosing stability control in elderly or paralyzed has motivated researchers to study how a stability control system works and how to determine its state at every time instant. Studying the stability of a human body is not only an important problem from a scientific viewpoint, but also finally leads to new designs of prostheses and orthoses and rehabilitation methods. Computer modeling enables researchers to study and describe the reactions and propose a suitable and optimized motion pattern to strengthen the neuromuscular system and helps a human body maintain its stability. A perturbation as a tilting is exposed to an underfoot plate of a musculoskeletal model of the body to study the stability. The studied model of a human body included four links and three degrees of freedom with eight muscles in the sagittal plane. Lagrangian dynamics was used for deriving equations of motion and muscles were modeled using Hill’s model. Using experimental data of joint trajectories for a human body under tilting perturbation, forward dynamics has been applied to predict joint trajectories and muscle activation. This study investigated the effects of stability on predicting body joints’ motion. A new stability function for a human body, based on the zero moment point, has been employed in a forward dynamics procedure using a direct collocation method. A multi-objective optimization based on genetic algorithm has been proposed to employ stability as a robotic objective function along with muscle stresses as a biological objective function. The obtained results for joints’ motion were compared to experimental data. The results show that, for this type of perturbations, muscle stresses are in conflict with body stability. This means that more body stability requires more stresses in muscles and reverse. Results also show the effects of the stability objective function in better prediction of joint trajectories.

MSC:

70E60 Robot dynamics and control of rigid bodies
92C10 Biomechanics

Software:

AnyBody
Full Text: DOI

References:

[1] Qu, X., Nussbaum, M.A., Madigan, M.L.: A balance control model of quiet upright stance based on an optimal control strategy. J. Biomech. 40, 3590-3597 (2007) · doi:10.1016/j.jbiomech.2007.06.003
[2] Jacobs, R., Burleigh-Jacobs, A.: Neural Muscular Control Strategies in Postural Coordination. Springer, Berlin/Heidelberg/New York (1998)
[3] van der Kooij, H., Jacobs, R., Koopman, B., Grootenboer, H.: A multisensory integration model of human stance control. Biol. Cybern. 80, 299-308 (1999) · Zbl 0932.92009 · doi:10.1007/s004220050527
[4] Allum, J.H., Adkin, A.L., Carpenter, M.G., Heldziolkowska, M., Honegger, F., Pierchala, K.: Trunk sway measures of postural stability during clinical balance tests: effects of a unilateral vestibular deficit. Gait Posture 14, 227-237 (2001) · doi:10.1016/S0966-6362(01)00132-1
[5] Le, C.K., Riach, C.: Postural stability measures: what to measure and for how long. Clin. Biomech. 11(3), 176-178 (1996) · doi:10.1016/0268-0033(95)00027-5
[6] Shimizu, Y., Thurner, S., Ehrenberger, K.: Multifractal spectra as a measure of complexity in human posture. Fractals 10(1), 103-116 (2002) · doi:10.1142/S0218348X02001130
[7] Winter, D.A.: Human balance and posture control during standing and walking. Gait Posture 3, 193-214 (1995) · doi:10.1016/0966-6362(96)82849-9
[8] Matjacic, Z.: A multi-purpose rehabilitation frame: an apparatus for experimental investigations of human balance a postural control. J. Med. Eng. Technol. 24(6), 250-254 (2000) · doi:10.1080/030919000300037186
[9] Nashner, L.M.: Fixed patterns of rapid postural responses among leg muscles during stance. Exp. Brain Res. 30, 13-24 (1977) · doi:10.1007/BF00237855
[10] Horak, F.B., Nashner, L.M.: Two distinct strategies for stance posture control: adaptation to altered support surface configurations. Neurosci. Abstr. 9, 65 (1983)
[11] Kuo, A.D., Zajac, F.E.: Human standing posture: multi-joint movement strategies based on biomechanical constraints. Prog. Brain Res. 97, 349-358 (2000) · doi:10.1016/S0079-6123(08)62294-3
[12] Iqbal, K., Pai, Y.C.: Predicted region of stability for balance recovery: motion and the knee joint can improve termination of forward movement. J. Biomech. 33(12), 1619-1627 (2000) · doi:10.1016/S0021-9290(00)00129-9
[13] Henry, S.M., Fung, J., Horak, F.B.: Control of stance during lateral and anterior/posterior surface translations. IEEE Trans. Rehabil. Eng. 6(1), 32-42 (1998) · doi:10.1109/86.662618
[14] Pai, Y.C., Iqbal, K.: Simulated movement termination for balance recovery: can movement strategies be sought to maintain stability even in the pressure of slipping or force sliding? J. Biomech. 32, 779-786 (1999) · doi:10.1016/S0021-9290(99)00074-3
[15] Consiglieri, L., Pires, E.B.: Analytical approach for the evaluation of the torques using inverse multibody dynamics. Multibody Syst. Dyn. 18, 471-483 (2007) · Zbl 1178.70072 · doi:10.1007/s11044-007-9046-6
[16] Naderi, D., Pasha Zanoosi, A.A., Sadeghi-Mehr, M.: Forward dynamics simulation of human body under tilting perturbations. Commun. Nonlinear Sci. Numer. Simul. 17, 1055-1064 (2012) · doi:10.1016/j.cnsns.2011.06.036
[17] Xiang, Y., Arora, J.S., Rahmatalla, S., Bhatt, R., Marler, T., Abdel-Malek, K.: Human lifting simulation using multi-objective optimization approach. Multibody Syst. Dyn. 23(4), 431-451 (2009) · Zbl 1320.70005 · doi:10.1007/s11044-009-9186-y
[18] Zajaca, F.E., Neptunea, R.R., Kautza, S.A.: Biomechanics and muscle coordination of human walking: Part II: Lessons from dynamical simulations and clinical implications. Gait Posture 17, 1-17 (2003) · doi:10.1016/S0966-6362(02)00069-3
[19] Hurmuzlu, Y., Basdogan, C.: On the measurement of dynamic stability of human locomotion. J. Biomech. Eng. 116(1), 30-36 (1994) · doi:10.1115/1.2895701
[20] Yamasaki, T., Nomura, T., Sato, S.: Phase reset and dynamic stability during human gait. Biosystems 71(1-2), 221-232 (2003) · doi:10.1016/S0303-2647(03)00118-7
[21] Süptitz, F., Moreno Catalá, M., Brüggemann, G.-P., Karamanidis, K.: Dynamic stability control during perturbed walking can be assessed by a reduced kinematic model across the adult female lifespan. Hum. Mov. Sci. 32(6), 1404-1414 (2013) · doi:10.1016/j.humov.2013.07.008
[22] Chagdes, J.R., Rietdyk, S., Haddad Jeffrey, M., Zelaznik Howard, N., Raman, A.: Dynamic stability of a human standing on a balance board. J. Biomech. 46(15), 2593-2602 (2013) · doi:10.1016/j.jbiomech.2013.08.012
[23] Beurskens, R., Wilken, J.M., Dingwell, J.B.: Dynamic stability of individuals with transtibial amputation walking in destabilizing environments. J. Biomech. 47(7), 1675-1681 (2014) · doi:10.1016/j.jbiomech.2014.02.033
[24] McAndrew Young, P.M., Wilken, J.M., Dingwell, J.B.: Dynamic margins of stability during human walking in destabilizing environments. J. Biomech. 45(6), 1053-1059 (2012) · doi:10.1016/j.jbiomech.2011.12.027
[25] McAndrew Younga, P.M., Dingwell, J.B.: Voluntarily changing step length or step width affects dynamic stability of human walking. Gait Posture 35(3), 472-477 (2012) · doi:10.1016/j.gaitpost.2011.11.010
[26] Dingwell, J.B., Marin, L.C.: Kinematic variability and local dynamic stability of upper body motions when walking at different speeds. J. Biomech. 39(3), 444-452 (2006) · doi:10.1016/j.jbiomech.2004.12.014
[27] Wilken, J.M., Dingwell, J.B., McAndrewa, P.M.: Dynamic stability of human walking in visually and mechanically destabilizing environments. J. Biomech. 44(4), 644-649 (2011) · doi:10.1016/j.jbiomech.2010.11.007
[28] Dingwell, J.B., Kang, H.G., Marin, L.C.: The effects of sensory loss and walking speed on the orbital dynamic stability of human walking. J. Biomech. 40(9), 1723-1730 (2007) · doi:10.1016/j.jbiomech.2006.08.006
[29] Winter, D.A.: Biomechanics and Motor Control of Human Movement. Wiley, New York (2005)
[30] Naderi, D., Miripour Fard, B., Sadeghi-Mehr, M.: Optimal prediction of human postural response under anterior-posterior platform tilting. Commun. Nonlinear Sci. Numer. Simul. 18, 99-108 (2013) · Zbl 1322.92003 · doi:10.1016/j.cnsns.2012.06.010
[31] Garner, B.A., Pandy, M.G.: Estimation of musculotendon properties in the human upper limb. Ann. Biomech. Eng. 31, 207-220 (2003) · doi:10.1114/1.1540105
[32] Van Soest, A.J., Bobbert, M.F.: The contributions of muscle properties in the control of explosive movements. Biol. Cybern. 69(3), 195-204 (1993) · doi:10.1007/BF00198959
[33] Delp, S.L.: Surgery simulation: a computer graphics system to analyze and design musculoskeletal reconstructions of the lower limb. Dissertation, Stanford University, CA, USA (1990)
[34] Van Mow, C., Huiskes, R.: Basic Orthopaedic Biomechanics and Mechano-Biology. Lippincott, Philadelphia (1997)
[35] Millard, M., Uchida, T., Seth, A., Delp Scott, L.: Flexing computational muscle: modeling and simulation of musculotendon dynamics. J. Biomech. Eng. 135, 0210051-02100511 (2013) · doi:10.1115/1.4023390
[36] Steele, K.M., Seth, A., Hicks, J.L., Schwartz, M.S., Delp, S.L.: Muscle contributions to support and progression during single-limb stance in crouch gait. J. Biomech. 43, 2099-2105 (2010) · doi:10.1016/j.jbiomech.2010.04.003
[37] Chand, T.J., Anderson, F.C., Higginson, J.S., Delp, S.L.: Stabilization of walking by intrinsic muscle properties revealed in a three-dimensional muscle-driven simulation. Comput. Methods Biomech. Biomed. Eng. 16, 451-462 (2013) · doi:10.1080/10255842.2011.627560
[38] Allison, A.S., Thelen, D.G., Schwartz, M.H., Anderson, F.C., Delp, S.L.: Muscular coordination of knee motion during the terminal swing phase of normal gait. J. Biomech. 40, 3314-3324 (2007) · doi:10.1016/j.jbiomech.2007.05.006
[39] Anderson, F.C., Pandy, M.G.: Static and dynamic optimization solutions for gait are practically equivalent. J. Biomech. 34, 153-161 (2001) · doi:10.1016/S0021-9290(00)00155-X
[40] Seth, A., Pandy, M.G.: A neuromusculoskeletal tracking method for estimating individual muscle forces in human movement. J. Biomech. 40, 356-366 (2007) · doi:10.1016/j.jbiomech.2005.12.017
[41] Lim, Y.P., Lin, Y.-C., Pandy, M.G.: Muscle function during gait is invariant to age when walking speed is controlled. Gait Posture 38, 253-259 (2013) · doi:10.1016/j.gaitpost.2012.11.020
[42] Anderson, F.C., Pandy, M.G.: Individual muscle contributions to support in normal walking. Gait Posture 17, 159-169 (2003) · doi:10.1016/S0966-6362(02)00073-5
[43] Pandy, M.G., Anderson, F.C.: Dynamic optimization of human gait. J. Biomech. 31, 115 (1998) · doi:10.1016/S0021-9290(98)80232-7
[44] Anderson, F.C., Ziegler, J.M., Pandy, M.G., Whalen, R.T.: Dynamic optimization of large-scale musculoskeletal systems. J. Biomech. 27, 773 (1994) · doi:10.1016/0021-9290(94)91257-2
[45] Yamaguchi, G.T., Pandy, M.G., Zajac, F.E.: Dynamic musculoskeletal models of human locomotion: perspectives on model formulation and control. Adv. Psychol. 78, 205-240 (1991) · doi:10.1016/S0166-4115(08)60744-X
[46] Damsgaard, M., Rasmussen, J., Turholm Christensen, S., Surma, E., de Zee, M.: Analysis of musculoskeletal systems in the AnyBody modeling system. Simul. Model. Pract. Theory 14, 1100-1111 (2006) · doi:10.1016/j.simpat.2006.09.001
[47] Schiehlen, W., García-Vallejo, D.: Walking dynamics from mechanism models to parameter optimization. Proc. IUTAM 2, 199-211 (2011) · doi:10.1016/j.piutam.2011.04.020
[48] Seth, A., Sherman, M., Reinbolt, J.A., Delp, S.L.: OpenSim: a musculoskeletal modeling and simulation framework for in silico investigations and exchange. Proc. IUTAM 2, 212-232 (2011) · doi:10.1016/j.piutam.2011.04.021
[49] Sherman, M.A., Seth, A., Delp, S.L.: Simbody: multibody dynamics for biomedical research. Proc. IUTAM 2, 241-261 (2011) · doi:10.1016/j.piutam.2011.04.023
[50] Mansouri, M., Reinbolt, J.A.: A platform for dynamic simulation and control of movement based on OpenSim and MATLAB. J. Biomech. 45, 1517-1521 (2012) · doi:10.1016/j.jbiomech.2012.03.016
[51] Reinbolt, J.A., Seth, A., Delp, S.L.: Simulation of human movement: applications using OpenSim. Proc. IUTAM 2, 186-198 (2011) · doi:10.1016/j.piutam.2011.04.019
[52] Yamaguchi, G.T., Moran, D.W., Si, J.: A computationally efficient method for solving the redundant problem in biomechanics. J. Biomech. 28, 999-1005 (1995) · doi:10.1016/0021-9290(94)00145-T
[53] Schiehlen, W.: Advanced Multibody System Dynamics: Simulation and Software Tools. Kluwer, Norwell (1993) · Zbl 0790.00004 · doi:10.1007/978-94-017-0625-4
[54] Schiehlen, W.: Multibody Systems Handbook. Springer, Berlin (1990) · Zbl 0703.70002 · doi:10.1007/978-3-642-50995-7
[55] Haug, E.: Computer Aided Kinematics and Dynamics of Mechanical Systems: Basic Methods. Allyn and Bacon, Boston (1989)
[56] Hardt, M.W., von Stryk, O.: Dynamic modeling in the simulation, optimization and control of bipedal and quadrupedal robots. Z. Angew. Math. Mech. 83(10), 648-662 (2003) · Zbl 1063.70006 · doi:10.1002/zamm.200310068
[57] Von Stryk, O., Bulirsch, R.: Direct and indirect methods for trajectory optimization. Ann. Oper. Res. 37, 357-373 (1992) · Zbl 0784.49023 · doi:10.1007/BF02071065
[58] Zlatnik, D.: Intelligently controlled above knee prosthesis. PhD thesis, ETH, Zurich (1998)
[59] Hatze, H.: The complete optimization of a human motion. Math. Biosci. 28, 99-135 (1976) · Zbl 0331.92003 · doi:10.1016/0025-5564(76)90098-5
[60] Gilchrist, L., Winter, D.: A two-part, viscoelastic foot model for use in gait simulations. J. Biomech. 29(6), 795-798 (1996) · doi:10.1016/0021-9290(95)00141-7
[61] Anderson, F.C., Pandy, M.G.: A dynamic optimization solution for vertical jumping in three dimensions. Comput. Methods Biomech. Biomed. Eng. 2, 201-231 (1999) · doi:10.1080/10255849908907988
[62] Neptune, R.R., Hull, M.L.: A theoretical analysis of preferred pedaling rate selection in endurance cycling. J. Biomech. 32, 409-415 (1999) · doi:10.1016/S0021-9290(98)00182-1
[63] von Stryk, O., Bulirsch, R.: Direct and indirect methods for trajectory optimization. Ann. Oper. Res. 37, 357-373 (1992) · Zbl 0784.49023 · doi:10.1007/BF02071065
[64] Betts, J.: Practical Methods for Optimal Control Using Nonlinear Programming. SIAM, Philadelphia (2001) · Zbl 0995.49017
[65] Fujimoto, Y., Kawamura, A.: Simulation of an autonomous biped walking robot including environmental force interaction. IEEE Robot. Autom. Mag. 5(2), 33-42 (1998) · doi:10.1109/100.692339
[66] Hardt, M.; Stryk, O., The role of motion dynamics in the design, control and stability of bipedal and quadrupedal robots, Fukuoka, Japan
[67] Vukobratovic, M., Juricic, D.: Contributions to the synthesis of biped gait. IEEE Trans. Biomed. Eng. 16, 1-6 (1969) · doi:10.1109/TBME.1969.4502596
[68] Hemami, H., Golliday, C.L.: The inverted pendulum and biped stability. Math. Biosci. 34, 95-110 (1977) · doi:10.1016/0025-5564(77)90038-4
[69] Hirai, K.; Hirose, M.; Haikawa, Y.; Takenaka, T., The development of the Honda humanoid robot (1998), Washington
[70] Li, Q.; Takanishi, A.; Kato, I., Learning control for a biped walking robot with a trunk, 1771-1777 (1993), Los Alamitos
[71] Shih, C. L.; Li, Y. Z.; Churng, S.; Lee, T. T.; Gruver, W. A., Trajectory synthesis and physical admissibility for a biped robot during the single-support phase, 1646-1652 (1990)
[72] Takanishi, A.; Ishida, M.; Yamazaki, Y.; Kato, I., The realization of dynamic walking by the biped robot WL-10RD, 459-466 (1985), Tokyo
[73] Arakawa, T.; Fukuda, T., Natural motion generation of a biped locomotion robot using the hierarchical trajectory generation method consisting of GA, EP layers, No. 1, 211-216 (1997) · doi:10.1109/ROBOT.1997.620040
[74] Shih, C.L.: The dynamics and control of a biped walking robot with seven degrees of freedom. ASME J. Dyn. Sys Meas. Control 118, 683-690 (1996) · Zbl 0866.93066 · doi:10.1115/1.2802343
[75] Vukobratovic, M., Borovac, B., Surla, D., Stokic, D.: Scientific Fundamentals of Robotics, Biped Locomotion: Dynamics Stability, Control, and Application. Springer, New York (1990) · Zbl 0699.70002 · doi:10.1007/978-3-642-83006-8
[76] Xiang, Y., Arora, J.S., Rahmatalla, S., Bhatt, R., Marler, T., Abdel-Malek, K.: Human lifting simulation using multi-objective optimization approach. Multibody Syst. Dyn. 23(4), 431-451 (2009) · Zbl 1320.70005 · doi:10.1007/s11044-009-9186-y
[77] Xiang, Y., Chung, H.J., Kim, J.H., Bhatt, R., Marler, T., Rahmatalla, S., Yang, J., Arora, J.S., Abdel-Malek, K.: Predictive dynamics: an optimization-based novel approach for human motion simulation. Struct. Multidiscip. Optim. 41(3), 465-479 (2009) · Zbl 1274.70007 · doi:10.1007/s00158-009-0423-z
[78] Kim, J.H., Abdel-Malek, K., Yang, J., Marler, R.T.: Prediction and analysis of human motion dynamics performing various tasks. Int. J. Hum. Factors Model. Simul. 1(10), 69-117 (2006) · doi:10.1504/IJHFMS.2006.011683
[79] Yamaguchi, J.I., Takanishi, A., Kato, I.: Development of a biped walking robot compensating for three-axis moment by trunk motion. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (1993)
[80] Dasgupta, A., Nakamura, Y.: Making feasible walking motion of humanoid robots from human motion capture data. Paper presented at the IEEE International Conference on Robotics and Automation (1999)
[81] Li, Q., Takanishi, A., Kato, I.: A biped walking robot having a zmp measurement system using universal force-moment sensors. Paper presented at the IEEE/RSJ International Workshop on Intelligent Robots and Systems, Intelligence for Mechanical Systems. (1991)
[82] Park, J.H., Rhee, Y.K.: ZMP trajectory generation for reduced trunk motions of biped robots. Paper presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (1998)
[83] Takanishi, A., Takeya, T., Karaki, H., Kato, I.: A control method for dynamic biped walking under unknown external force. Paper presented at the IEEE International Workshop on Intelligent Robots and Systems, Towards a New Frontier of Applications (1990)
[84] Marler, R.T., Arora, J.S.: Survey of multi-objective optimization methods for engineering. Struct. Multidiscip. Optim. 26(6), 369-395 (2004) · Zbl 1243.90199 · doi:10.1007/s00158-003-0368-6
[85] Marler, T.: A Study of Multi-Objective Optimization Methods for Engineering Applications. VDM Verlag, Saarbrucken (2009)
[86] Marler, R.T., Arora, J.S., Yang, J., Kim, H.J., Abdel-Malek, K.: Use of multi-objective optimization for digital human posture prediction. Eng. Optim. 41(10), 295-943 (2009) · doi:10.1080/03052150902853013
[87] Goswami, A.: Postural stability of biped robots and the foot-rotation indicator (FRI) point. Int. J. Robot. Res. 18(6), 523-533 (1999) · doi:10.1177/02783649922066376
[88] Bachar, Y.: Developing controllers for biped humanoid locomotion. MSc thesis, School of Informatics, University of Edinburgh (2004)
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