Skip to main content

Advertisement

SpringerLink
Log in

Multibody dynamics modeling of human mandibular musculoskeletal system and its applications in surgical planning

  • Published:
Multibody System Dynamics Aims and scope Submit manuscript

Abstract

Many patients suffering from oral and maxillofacial tumors cannot open their mouths wide after mandibular reconstruction surgery. Musculoskeletal multibody modeling could be a valuable tool for predicting patient-specific jaw opening functions in the preoperative stage. In this study, a flexible multibody dynamics modeling framework of the human mandibular musculoskeletal system is proposed for surgical planning. In the model, the mandibular muscle bundles are discretized by a flexible cable element combining a typical Hill-type musculotendon model with distributed mass. The mandibular kinematics, together with the electromyographic activities of masticatory muscles, were measured in a patient with a unilateral mandibular tumor. Using the obtained experimental data, a forward–inverse dynamics procedure was proposed to realize the decoupled calculation of synergistic head movement and temporomandibular joint (TMJ) dynamics. The surgical planning simulation was driven by the measured activation patterns of the masticatory muscles and the calculated patterns of the jaw opening and pterygoid muscles. The muscle biomechanical parameters in the postoperative model were changed according to the medical imaging measurement of five patients before and after surgical interventions. As validation of the proposed surgical planning method, the predicted maximum jaw gape and mandibular deviations were compared with postoperative measurements. Numerical results further revealed the bistable characteristic of the TMJs together with the alternations of mandibular movement functions caused by muscle-release surgery. The proposed multibody simulation framework provides a novel method for understanding patient-specific pathology of suffering from trismus and assisting in designing treatments and rehabilitation strategies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Sung, H., Ferlay, J., Siegel, R.L., Laversanne, M., Soerjomataram, I., Jemal, A., Bray, F.: Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 71(3), 209–249 (2021)

    Google Scholar 

  2. Siegel, R.L., Miller, K.D., Fuchs, H.E., Jemal, A.: Cancer statistics, 2022. CA Cancer J. Clin. 72(1), 7–33 (2022)

    Google Scholar 

  3. Goh, B.T., Lee, S., Tideman, H., Stoelinga, P.J.: Mandibular reconstruction in adults: a review. Int. J. Oral Maxillofac. 37(7), 597–605 (2008)

    Google Scholar 

  4. Pauli, N., Olsson, C., Pettersson, N., Johansson, M., Haugen, H., Wilderäng, U., Steineck, G., Finizia, C.: Risk structures for radiation-induced trismus in head and neck cancer. Acta Oncol. 55(6), 788–792 (2016)

    Google Scholar 

  5. Watters, A.L., Cope, S., Keller, M.N., Padilla, M., Enciso, R.: Prevalence of trismus in patients with head and neck cancer: a systematic review with meta-analysis. Head Neck 41(9), 3408–3421 (2019)

    Google Scholar 

  6. Ishida, S., Shibuya, Y., Kobayashi, M., Komori, T.: Assessing stomatognathic performance after mandibulectomy according to the method of mandibular reconstruction. Int. J. Oral Maxillofac. Surg. 44(8), 948–955 (2015)

    Google Scholar 

  7. Curtis, D., Plesh, O., Hannam, A., Sharma, A., Curtis, T.: Modeling of jaw biomechanics in the reconstructed mandibulectomy patient. J. Prosthet. Dent. 81(2), 167–173 (1999)

    Google Scholar 

  8. Kuboki, T., Takenami, Y., Maekawa, K., Shinoda, M., Yamashita, A., Clark, G.T.: Biomechanical calculation of human TM joint loading with jaw opening. J. Oral Rehabil. 27(11), 940–951 (2000)

    Google Scholar 

  9. Röhrle, O., Waddell, J.N., Foster, K.D., Saini, H., Pullan, A.J.: Using a motion-capture system to record dynamic articulation for application in CAD/CAM software. J. Prosthodont. 18(8), 703–710 (2009)

    Google Scholar 

  10. Woodford, S.C., Robinson, D.L., Mehl, A., Lee, P., Ackland, D.C.: Measurement of normal and pathological mandibular and temporomandibular joint kinematics: a systematic review. J. Biomech. 111, 109994 (2020)

    Google Scholar 

  11. Zheng, K., Liao, Z., Yoda, N., Fang, J., Chen, J., Zhang, Z., Zhong, J., Peck, C., Sasaki, K., Swain, M.V., et al.: Investigation on masticatory muscular functionality following oral reconstruction–an inverse identification approach. J. Biomech. 90, 1–8 (2019)

    Google Scholar 

  12. Lindauer, S., Gay, T., Rendell, J.: Effect of jaw opening on masticatory muscle EMG-force characteristics. J. Dent. Res. 72(1), 51–55 (1993)

    Google Scholar 

  13. Baad-Hansen, L., Hara, S., Marumo, Y., Miles, T., Svensson, P.: Effect of experimental pain on EMG-activity in human jaw-closing muscles in different jaw positions. Arch. Oral Biol. 54(1), 32–39 (2009)

    Google Scholar 

  14. Hannam, A.: Current computational modelling trends in craniomandibular biomechanics and their clinical implications. J. Oral Rehabil. 38(3), 217–234 (2011)

    Google Scholar 

  15. Koolstra, J., van Eijden, T.: Dynamics of the human masticatory muscles during a jaw open-close movement. J. Biomech. 30(9), 883–889 (1997)

    Google Scholar 

  16. Koolstra, J., van Eijden, T.: The jaw open-close movements predicted by biomechanical modelling. J. Biomech. 30(9), 943–950 (1997)

    Google Scholar 

  17. Koolstra, J., van Eijden, T.: Functional significance of the coupling between head and jaw movements. J. Biomech. 37(9), 1387–1392 (2004)

    Google Scholar 

  18. Hannam, A.G., Stavness, I., Lloyd, J.E., Fels, S.: A dynamic model of jaw and hyoid biomechanics during chewing. J. Biomech. 41(5), 1069–1076 (2008)

    Google Scholar 

  19. Hannam, A.G., Stavness, I.K., Lloyd, J.E., Fels, S.S., Miller, A.J., Curtis, D.A.: A comparison of simulated jaw dynamics in models of segmental mandibular resection versus resection with alloplastic reconstruction. J. Prosthet. Dent. 104(3), 191–198 (2010)

    Google Scholar 

  20. Tuijt, M., Koolstra, J.H., Lobbezoo, F., Naeije, M.: Differences in loading of the temporomandibular joint during opening and closing of the jaw. J. Biomech. 43(6), 1048–1054 (2010)

    Google Scholar 

  21. Tuijt, M., Koolstra, J., Lobbezoo, F., Naeije, M.: How muscle relaxation and laterotrusion resolve open locks of the temporomandibular joint. Forward dynamic 3D-modeling of the human masticatory system. J. Biomech. 49(2), 276–283 (2016)

    Google Scholar 

  22. Koolstra, J., van Eijden, T.: Combined finite-element and rigid-body analysis of human jaw joint dynamics. J. Biomech. 38(12), 2431–2439 (2005)

    Google Scholar 

  23. Sagl, B., Schmid-Schwap, M., Piehslinger, E., Kundi, M., Stavness, I.: A dynamic jaw model with a finite-element temporomandibular joint. Front. Physiol. 10, 1156 (2019)

    Google Scholar 

  24. She, X., Sun, S., Damon, B.J., Hill, C.N., Coombs, M.C., Wei, F., Lecholop, M.K., Steed, M.B., Bacro, T.H., Slate, E.H., et al.: Sexual dimorphisms in three-dimensional masticatory muscle attachment morphometry regulates temporomandibular joint mechanics. J. Biomech. 126, 110623 (2021)

    Google Scholar 

  25. Killen, B.A., Falisse, A., De Groote, F., Jonkers, I.: In silico-enhanced treatment and rehabilitation planning for patients with musculoskeletal disorders: can musculoskeletal modelling and dynamic simulations really impact current clinical practice? Appl. Sci. 10(20), 7255 (2020)

    Google Scholar 

  26. Jalalian, A., Tay, F.E., Arastehfar, S., Liu, G.: A patient-specific multibody kinematic model for representation of the scoliotic spine movement in frontal plane of the human body. Multibody Syst. Dyn. 39(3), 197–220 (2017)

    Google Scholar 

  27. Hajizadeh, K., Huang, M., Gibson, I., Liu, G.: Developing a 3D multi-body model of a scoliotic spine during lateral bending for comparison of ribcage flexibility and lumbar joint loading to the normal model. In: ASME International Mechanical Engineering Congress and Exposition, vol. 56215, p. V03AT03A027. American Society of Mechanical Engineers, San Diego, California, USA (2013)

    Google Scholar 

  28. Hainisch, R., Gfoehler, M., Zubayer-Ul-Karim, M., Pandy, M.G.: Method for determining musculotendon parameters in subject-specific musculoskeletal models of children developed from MRI data. Multibody Syst. Dyn. 28(1), 143–156 (2012)

    Google Scholar 

  29. Shayestehpour, H., Rasmussen, J., Galibarov, P., Wong, C.: An articulated spine and ribcage kinematic model for simulation of scoliosis deformities. Multibody Syst. Dyn. 53(2), 115–134 (2021)

    Google Scholar 

  30. Shu, L., Yamamoto, K., Yao, J., Saraswat, P., Liu, Y., Mitsuishi, M., Sugita, N.: A subject-specific finite element musculoskeletal framework for mechanics analysis of a total knee replacement. J. Biomech. 77, 146–154 (2018)

    Google Scholar 

  31. Kebbach, M., Grawe, R., Geier, A., Winter, E., Bergschmidt, P., Kluess, D., D’Lima, D., Woernle, C., Bader, R.: Effect of surgical parameters on the biomechanical behaviour of bicondylar total knee endoprostheses – a robot-assisted test method based on a musculoskeletal model. Sci. Rep. 9(1), 1–11 (2019)

    Google Scholar 

  32. Eschweiler, J., Stromps, J.P., Fischer, M., Schick, F., Rath, B., Pallua, N., Radermacher, K.: Development of a biomechanical model of the wrist joint for patient-specific model guided surgical therapy planning: part 1. Proc. Inst. Mech. Eng. H 230(4), 310–325 (2016)

    Google Scholar 

  33. Eschweiler, J., Stromps, J.P., Fischer, M., Schick, F., Rath, B., Pallua, N., Radermacher, K.: A biomechanical model of the wrist joint for patient-specific model guided surgical therapy: part 2. Proc. Inst. Mech. Eng. H 230(4), 326–334 (2016)

    Google Scholar 

  34. Barone, S., Paoli, A., Razionale, A.V.: Creation of 3D multi-body orthodontic models by using independent imaging sensors. Sensors 13(2), 2033–2050 (2013)

    Google Scholar 

  35. Wang, S., Yang, J.: Simulating cranio-maxillofacial surgery based on mixed-element biomechanical modelling. Comput. Methods Biomech. Biomed. Eng. 13(3), 419–429 (2010)

    Google Scholar 

  36. Shahim, K., Jürgens, P., Cattin, P.C., Nolte, L.P., Reyes, M.: Prediction of cranio-maxillofacial surgical planning using an inverse soft tissue modelling approach. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 18–25. Springer, Berlin (2013)

    Google Scholar 

  37. Brosses, E.S.D., Areiza, D.A., Bonnet, A.S., Lipinski, P.: Subject-specific numerical estimation of the temporomandibular joint reaction force during mouth opening and closing movements. Comput. Methods Biomech. Biomed. Eng. 14(sup1), 125–127 (2011)

    Google Scholar 

  38. Vallejo, K.O., Sapin-de Brosses, E., Bonnet, A.S.: Electromyography of the masticatory muscles during biting. Comput. Methods Biomech. Biomed. Eng. 20(sup1), 155–156 (2017)

    Google Scholar 

  39. De Zee, M., Dalstra, M., Cattaneo, P.M., Rasmussen, J., Svensson, P., Melsen, B.: Validation of a musculo-skeletal model of the mandible and its application to mandibular distraction osteogenesis. J. Biomech. 40(6), 1192–1201 (2007)

    Google Scholar 

  40. De Zee, M., Cattaneo, P.M., Svensson, P., Pedersen, T.K., Melsen, B., Rasmussen, J., Dalstra, M.: Prediction of the articular eminence shape in a patient with unilateral hypoplasia of the right mandibular ramus before and after distraction osteogenesis—a simulation study. J. Biomech. 42(8), 1049–1053 (2009)

    Google Scholar 

  41. Andersen, M., De Zee, M., Damsgaard, M., Nolte, D., Rasmussen, J.: Introduction to force-dependent kinematics: theory and application to mandible modeling. J. Biomech. Eng. 139(9), 091001 (2017)

    Google Scholar 

  42. Zheng, K., Yoda, N., Chen, J., Liao, Z., Zhong, J., Wu, C., Wan, B., Koyama, S., Sasaki, K., Peck, C., et al.: Bone remodeling following mandibular reconstruction using fibula free flap. J. Biomech. 133, 110968 (2022)

    Google Scholar 

  43. Moon, H., Lee, S.K., Kim, W.M., Seo, Y.G.: Effects of exercise on cervical muscle strength and cross-sectional area in patients with thoracic hyperkyphosis and chronic cervical pain. Sci. Rep. 11(1), 1–9 (2021)

    Google Scholar 

  44. Baqaien, M., Al-Salti, F., Muessig, D.: Changes in condylar path inclination during maximum protrusion between the ages of 6 and 12 years. J. Oral Rehabil. 34(1), 27–33 (2007)

    Google Scholar 

  45. Challis, J.H.: A procedure for determining rigid body transformation parameters. J. Biomech. 28(6), 733–737 (1995)

    Google Scholar 

  46. Gallo, L., Salis Gross, S., Palla, S.: Nocturnal masseter EMG activity of healthy subjects in a natural environment. J. Dent. Res. 78(8), 1436–1444 (1999)

    Google Scholar 

  47. Guo, J., Huang, H., Yu, Y., Liang, Z., Ambrósio, J., Zhao, Z., Ren, G., Ao, Y.: Modeling muscle wrapping and mass flow using a mass-variable multibody formulation. Multibody Syst. Dyn. 49(3), 1–22 (2020)

    MathSciNet  MATH  Google Scholar 

  48. Lloyd, D.G., Besier, T.F.: An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. J. Biomech. 36(6), 765–776 (2003)

    Google Scholar 

  49. Quental, C., Folgado, J., Ambrósio, J., Monteiro, J.: A multibody biomechanical model of the upper limb including the shoulder girdle. Multibody Syst. Dyn. 28(1), 83–108 (2012)

    MathSciNet  Google Scholar 

  50. Thelen, D.G.: Adjustment of muscle mechanics model parameters to simulate dynamic contractions in older adults. J. Biomech. Eng. 125(1), 70–77 (2003)

    Google Scholar 

  51. Winters, J.M.: An improved muscle-reflex actuator for use in large-scale neuromusculoskeletal models. Ann. Biomed. Eng. 23(4), 359–374 (1995)

    Google Scholar 

  52. Cignoni, P., Callieri, M., Corsini, M., Dellepiane, M., Ganovelli, F., Ranzuglia, G., et al.: Meshlab: an open-source mesh processing tool. In: Eurographics Italian Chapter Conference, Vol. 2008, Salerno, Italy, pp. 129–136 (2008).

    Google Scholar 

  53. Stavness, I., Hannam, A.G., Lloyd, J.E., Fels, S.: An integrated dynamic jaw and laryngeal model constructed from ct data. In: International Symposium on Biomedical Simulation, pp. 169–177. Springer, Berlin (2006)

    Google Scholar 

  54. Hashimoto, T., Murakoshi, A., Kikuchi, T., Michiwaki, Y., Koike, T.: Development of musculoskeletal model for the hyoid bone during swallowing. In: 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), pp. 457–460. IEEE, Las Vegas, NV, USA (2016)

    Google Scholar 

  55. Millard, M., Uchida, T., Seth, A., Delp, S.L.: Flexing computational muscle: modeling and simulation of musculotendon dynamics. J. Biomech. Eng. 135(2), 021005 (2013)

    Google Scholar 

  56. Peng, Y., Wei, Y., Zhou, M.: Efficient modeling of cable–pulley system with friction based on arbitrary-Lagrangian–Eulerian approach. Appl. Math. Mech. 38(12), 1785–1802 (2017)

    MathSciNet  Google Scholar 

  57. Guo, J., Sun, Y., Hao, Y., Cui, L., Ren, G.: A mass-flowing muscle model with shape restrictive soft tissues: correlation with sonoelastography. Biomech. Model. Mechanobiol. 19(3), 911–926 (2020)

    Google Scholar 

  58. Zajac, F.E.: Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Crit. Rev. Biomed. Eng. 17(4), 359–411 (1989)

    Google Scholar 

  59. Silva, M.P.T., Ambrósio, J.A.C.: Solution of redundant muscle forces in human locomotion with multibody dynamics and optimization tools. Mech. Based Des. Struct. Mach. 31(3), 381–411 (2003)

    Google Scholar 

  60. Winters, T.M., Takahashi, M., Lieber, R.L., Ward, S.R.: Whole muscle length-tension relationships are accurately modeled as scaled sarcomeres in rabbit hindlimb muscles. J. Biomech. 44(1), 109–115 (2011)

    Google Scholar 

  61. Millard, M., Delp, S.: A computationally efficient muscle model. In: Summer Bioengineering Conference, vol. 44809, pp. 1055–1056. American Society of Mechanical Engineers, Fajardo, Puerto Rico, USA (2012)

    Google Scholar 

  62. van Eijden, T., Korfage, J., Brugman, P.: Architecture of the human jaw-closing and jaw-opening muscles. Anat. Rec. 248(3), 464–474 (1997)

    Google Scholar 

  63. Günther, M., Schmitt, S., Wank, V.: High-frequency oscillations as a consequence of neglected serial damping in Hill-type muscle models. Biol. Cybern. 97(1), 63–79 (2007)

    MATH  Google Scholar 

  64. Blankevoort, L., Kuiper, J., Huiskes, R., Grootenboer, H.: Articular contact in a three-dimensional model of the knee. J. Biomech. 24(11), 1019–1031 (1991)

    Google Scholar 

  65. Amberg, B., Romdhani, S., Vetter, T.: Optimal step nonrigid ICP algorithms for surface registration. In: Computer Vision and Pattern Recognition, 2007. CVPR’07. IEEE Conference on, pp. 1–8. IEEE, Minneapolis, MN, USA (2007)

    Google Scholar 

  66. Pellikaan, P., van der Krogt, M., Carbone, V., Fluit, R., Vigneron, L., Van Deun, J., Verdonschot, N., Koopman, H.F.: Evaluation of a morphing based method to estimate muscle attachment sites of the lower extremity. J. Biomech. 47(5), 1144–1150 (2014)

    Google Scholar 

  67. Peck, C., Langenbach, G., Hannam, A.: Dynamic simulation of muscle and articular properties during human wide jaw opening. Arch. Oral Biol. 45(11), 963–982 (2000)

    Google Scholar 

  68. Modenese, L., Renault, J.B.: Automatic generation of personalised skeletal models of the lower limb from three-dimensional bone geometries. J. Biomech. 116, 110186 (2021)

    Google Scholar 

  69. Flores, P., Ambrósio, J.: On the contact detection for contact-impact analysis in multibody systems. Multibody Syst. Dyn. 24(1), 103–122 (2010)

    MathSciNet  MATH  Google Scholar 

  70. May, M.M., Howe, B.M., O’Byrne, T.J., Alexander, A.E., Morris, J.M., Moore, E.J., Kasperbauer, J.L., Janus, J.R., Van Abel, K.M., Dickens, H.J., Price, D.L.: Short and long-term outcomes of three-dimensional printed surgical guides and virtual surgical planning versus conventional methods for fibula free flap reconstruction of the mandible: decreased nonunion and complication rates. Head Neck 43(8), 2342–2352 (2021)

    Google Scholar 

  71. Endo, N.: Studies on masticatory functions in patients with surgical mandibular reconstruction. Oral Surg. Oral Med. Oral Pathol. Oral Radiol. Endo. 34(3), 390–407 (1972)

    Google Scholar 

  72. Wang, L., Su, Y., Zheng, G., Liao, G., Zhang, W.: Healing masseter entheses of mandibular reconstruction with autograft—Raman spectroscopic and histological study. Int. J. Oral Maxillofac. Surg. 42(7), 915–922 (2013)

    Google Scholar 

  73. Eriksson, P.O., Zafar, H., Nordh, E.: Concomitant mandibular and head-neck movements during jaw opening–closing in man. J. Oral Rehabil. 25(11), 859–870 (1998)

    Google Scholar 

  74. Zafar, H., Nordh, E., Eriksson, P.O.: Temporal coordination between mandibular and head–neck movements during jaw opening–closing tasks in man. Arch. Oral Biol. 45(8), 675–682 (2000)

    Google Scholar 

  75. Domire, Z.J., Challis, J.H.: The influence of an elastic tendon on the force producing capabilities of a muscle during dynamic movements. Comput. Methods Biomech. Biomed. Eng. 10(5), 337–341 (2007)

    Google Scholar 

  76. Guess, T.M.: Forward dynamics simulation using a natural knee with menisci in the multibody framework. Multibody Syst. Dyn. 28(1), 37–53 (2012)

    Google Scholar 

  77. Guo, J., Guo, W., Ren, G.: Embodiment of intra-abdominal pressure in a flexible multibody model of the trunk and the spinal unloading effects during static lifting tasks. Biomech. Model. Mechanobiol. 20, 1599–1626 (2021)

    Google Scholar 

  78. Guo, J., Chen, J., Wang, J., Ren, G., Tian, Q., Guo, C.: EMG-assisted forward dynamics simulation of subject-specific mandible musculoskeletal system. J. Biomech. 139, 111143 (2022)

    Google Scholar 

  79. Woźniak, K., Szyszka-Sommerfeld, L., Lichota, D.: The electrical activity of the temporal and masseter muscles in patients with TMD and unilateral posterior crossbite. BioMed Res. Int. 2015, 259372 (2015)

    Google Scholar 

  80. Kurasawa, I., Tsuchiya, S., Amari, M., Yanagida, F.: EMG activity in the TMD patient with self-sustained discharge in closing muscles: evaluation of motoneuron “bistability”. J. Jpn. Soc. Temporomand. Jt. 14(3), 286–290 (2002) (in Japanese)

    Google Scholar 

  81. Rubin, C.T., Lanyon, L.E., et al.: Regulation of bone formation by applied dynamic loads. J. Bone Jt. Surg., Am. 66(3), 397–402 (1984)

    Google Scholar 

  82. Rong, Q., Lenz, J., Schweizerhof, K., Schindler, H., Riediger, D.: Simulation of bone modeling around a screw implant in the mandible. In: PAMM: Proceedings in Applied Mathematics and Mechanics, vol. 2, pp. 254–255. Wiley Online Library, Berlin, Germany (2003)

    MATH  Google Scholar 

  83. Sun, Y., Lim, C.M., Tan, H.H., Ren, H.: Soft oral interventional rehabilitation robot based on low-profile soft pneumatic actuator. In: 2015 IEEE International Conference on Robotics and Automation (ICRA), pp. 2907–2912. IEEE, Seattle, WA, USA (2015)

    Google Scholar 

  84. Gupta, U., Wang, Y., Ren, H., Zhu, J.: Dynamic modeling and feedforward control of jaw movements driven by viscoelastic artificial muscles. IEEE/ASME Trans. Mechatron. 24(1), 25–35 (2018)

    Google Scholar 

  85. Hiasa, Y., Otake, Y., Takao, M., Ogawa, T., Sugano, N., Sato, Y.: Automated muscle segmentation from clinical CT using Bayesian U-Net for personalized musculoskeletal modeling. IEEE Trans. Med. Imaging 39(4), 1030–1040 (2019)

    Google Scholar 

  86. Korcari, A., Buckley, M.R., Loiselle, A.E.: Characterization of scar tissue biomechanics during adult murine flexor tendon healing. J. Mech. Behav. Biomed. Mater. 130, 105192 (2022)

    Google Scholar 

  87. Buesa-Bárez, J.M., Martín-Ares, M., Martínez-Rodríguez, N., Barona-Dorado, C., Sanz-Alonso, J., Cortés-Bretón-Brinkmann, J., Martínez-González, J.M.: Masseter and temporalis muscle electromyography findings after lower third molar extraction. Med. Oral Patol. Oral Cir. Bucal 23(1), e92 (2018)

    Google Scholar 

  88. Wang, J., Chen, J., Wang, Y., Xu, X., Guo, C.: Application of digital mandibular movement record and masticatory muscle electromyography in the evaluation of stomatognathic function in patients with mandibular tumor. J. Peking Univ. (Health Sci.) 51(3), 571 (2019) (in Chinese)

    Google Scholar 

  89. Zhu, M., Yu, B., Yang, W., Jiang, Y., Lu, L., Huang, Z., Chen, S., Li, G.: Evaluation of normal swallowing functions by using dynamic high-density surface electromyography maps. Biomed. Eng. Online 16, 133 (2017)

    Google Scholar 

  90. Anderson, F.C., Pandy, M.G.: Dynamic optimization of human walking. J. Biomech. Eng. 123(5), 381–390 (2001)

    Google Scholar 

  91. Quental, C., Folgado, J., Ambrósio, J.: A window moving inverse dynamics optimization for biomechanics of motion. Multibody Syst. Dyn. 38(2), 157–171 (2016)

    Google Scholar 

  92. Shourijeh, M.S., Mehrabi, N., McPhee, J.: Forward static optimization in dynamic simulation of human musculoskeletal systems: a proof-of-concept study. J. Comput. Nonlinear Dyn. 12(5), 051005 (2017)

    Google Scholar 

  93. Bottasso, C.L., Prilutsky, B.I., Croce, A., Imberti, E., Sartirana, S.: A numerical procedure for inferring from experimental data the optimization cost functions using a multibody model of the neuro-musculoskeletal system. Multibody Syst. Dyn. 16(2), 123–154 (2006)

    MathSciNet  MATH  Google Scholar 

  94. Röhrle, O., Pullan, A.J.: Three-dimensional finite element modelling of muscle forces during mastication. J. Biomech. 40(15), 3363–3372 (2007)

    Google Scholar 

  95. Han, M., Hong, J., Park, F.: Musculoskeletal dynamics simulation using shape-varying muscle mass models. Multibody Syst. Dyn. 33(4), 367–388 (2015)

    MathSciNet  Google Scholar 

  96. Gfrerer, M., Simeon, B.: Fiber-based modeling and simulation of skeletal muscles. Multibody Syst. Dyn. 52(1), 1–30 (2021)

    MathSciNet  MATH  Google Scholar 

  97. Gantoi, F.M., Brown, M.A., Shabana, A.A.: Finite element modeling of the contact geometry and deformation in biomechanics applications. J. Comput. Nonlinear Dyn. 8(4), 041013 (2013)

    Google Scholar 

  98. Mikkola, A., Shabana, A.A., Sanchez-Rebollo, C., Jimenez-Octavio, J.R.: Comparison between ANCF and B-spline surfaces. Multibody Syst. Dyn. 30(2), 119–138 (2013)

    MathSciNet  Google Scholar 

  99. Chang, H., Liu, C., Tian, Q., Hu, H., Mikkola, A.: Three new triangular shell elements of ANCF represented by Bézier triangles. Multibody Syst. Dyn. 35(4), 321–351 (2015)

    MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

This work was partly supported by the National Key R&D Program of China (2019YFB1311304), National Natural Science Foundations of China (12102035, 12125201), Beijing Natural Science Foundation (L212008), and Peking University Medicine Fund for world’s leading discipline or discipline cluster development (BMU2022XKQ003).

Author information

Authors and Affiliations

  1. MOE Key Laboratory of Dynamics and Control of Flight Vehicle, School of Aerospace Engineering, Beijing Institute of Technology, Beijing, 100081, People’s Republic of China

    Jianqiao Guo & Qiang Tian

  2. Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology, Beijing, 100081, People’s Republic of China

    Jing Wang, Junpeng Chen & Chuanbin Guo

  3. National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing Key Laboratory of Digital Stomatology, Peking University School and Hospital of Stomatology, Beijing, 100081, People’s Republic of China

    Jing Wang, Junpeng Chen & Chuanbin Guo

  4. Department of Engineering Mechanics, Tsinghua University, Beijing, 100084, People’s Republic of China

    Gexue Ren

Authors
  1. Jianqiao Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jing Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Junpeng Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gexue Ren
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Qiang Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Chuanbin Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Jianqiao Guo and Jing Wang contributed equally to this work as first authors. Jianqiao Guo, Qiang Tian, and Gexue Ren designed and developed the software used in analysis; Jing Wang, Junpeng Chen, and Chuanbin Guo conceived and designed the experiments; Jing Wang, and Junpeng Chen performed the experiments; Jianqiao Guo, Jing Wang, and Junpeng Chen wrote the paper; Gexue Ren, Qiang Tian, and Chuanbin Guo revised the paper. All authors gave final approval for publication.

Corresponding author

Correspondence to Jianqiao Guo.

Ethics declarations

Competing Interests

The authors declare that they have no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Guo, J., Wang, J., Chen, J. et al. Multibody dynamics modeling of human mandibular musculoskeletal system and its applications in surgical planning. Multibody Syst Dyn 57, 299–325 (2023). https://doi.org/10.1007/s11044-023-09876-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11044-023-09876-x

Keywords

Search

Navigation