人体骨肌系统的整体生物力学建模与仿真分析研究
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摘要
人体骨肌系统是实现人体各种运动的生理物质基础,是人体同外界进行动力学交互作用的根本,同时也是人体其它器官和系统的基本生存条件,其宏观上的主要特性表现为与运动和力相关的动力学问题。因此对人体骨肌系统进行力学方面的研究具有非常重要的意义。
本文基于研究所承担的国家自然科学基金重点项目“中国力学虚拟人”,在中国可视人项目冷冻切片数据集的基础上,通过计算机虚拟技术、力学建模及分析技术、以及有限元建模及分析技术建立了一个人体骨肌系统生物力学计算平台。该平台主要包括人体骨肌系统的三维建模与系统集成模块、人体骨肌系统的运动学与动力学建模及系统集成模块、以及人体骨肌系统的有限元建模与系统集成模块等三大部分。重点针对中国力学虚拟人系统集成中的一些关键技术进行了研究,完成了力学虚拟人以上三大模块的系统集成开发,实现了力学虚拟人计算平台的功能。本文的主要工作可以归纳为以下几点:
1.基于人体解剖学特征结构,完成了中国力学虚拟人三维模型的系统集成和软件开发。一个完整的人体骨骼-肌肉模型是中国力学虚拟人课题的研究基础。为此,本文对由中国数字人冷冻切片数据库所建立起来的人体各部分模型进行了系统集成与软件开发。根据解剖学的要求,建立了虚拟人体整体坐标系统,对虚拟人各部分模型进行了坐标转换,对关节接触部分进行了解剖学运动关系的定义。根据肌肉力学虚拟线在骨骼上的附着位置,将肌肉力虚拟线模型装配在了虚拟人骨骼模型上,建立了能够反映真实人体骨肌系统解剖特性的三维模型。在Microsoft VisualStudio 2005环境下,开发了力学虚拟人三维模型仿真软件,实现了力学虚拟人三维几何模型的系统集成与仿真。
2.完成了中国力学虚拟人运动学与动力学模块的系统集成与开发。结合NDI运动捕捉系统,以基于人体测量学数据和特殊标记点(Marker)分布的算法,开发了力学虚拟人运动捕捉与分析模块,解决了该模块同运动捕捉硬件系统、动力学分析模块之间的数据接口问题。
3.对小波分析方法在人体骨肌系统EMG信号处理及肌肉力预测中的应用问题进行了探索性的研究。提出了一种基于小波理论的动态EMG信号预测肌肉力的方法。通过对举重运动员的举重动作进行运动捕捉实验、反向动力学建模以及分析,对肱二头肌、肱三头肌以及三角肌进行EMG信号测量,利用所提出的方法进行了肌肉力预测。经过对比,预测结果同反向动力学的预测结果相一致,验证了该方法的可用性。同时探索研究了利用模态综合方法来分析人体骨骼的振动特性和应变等问题,对人体步态进行了实验测量与分析,获得了较好的结果。
4.基于并行计算技术,建立了中国力学虚拟人系统集成有限元模型。根据人体关节联结的生理学和解剖学特性,对人体各部分的有限元模型进行系统集成建模。建立了踝关节、膝关节、髋关节、骶髂关节、肩关节、肘关节等部分的有限元连接模型,利用弹簧单元和连接单元对关节连接处的韧带和软骨进行了有限元建模。根据中国力学虚拟人骨肌系统三维整体模型,建立了有限元模型中的肌肉力载荷集,在下肢、上肢以及胸腰部分定义了肌肉力载荷集,用来模拟人体运动过程中,作用在骨骼上的肌肉力对骨骼系统应力分布的影响。
5.对人体的弯腰搬物动作进行了运动捕捉实验,将整个运动过程分为4个运动相位,建立了每个相位的有限元整体模型。基于运动学与动力学模块的分析计算结果,在上海超级计算中心的曙光4000A超级并行计算平台上,对人体弯腰搬物动作进行了整体有限元模型的仿真计算。针对本文所建立的人体骨肌系统总体有限元模型,对不同的并行计算方案进行了测试,确定了并行效率最佳的并行算法和硬件配置。通过对计算结果的比较分析,论证了中国力学虚拟人集成计算平台的可靠性。
Human musculoskeletal system is the requisite part for human movement in daily life. It is also fundamental for the interaction between human body with outside environment, and provide the subsistence for the organs. It is very important to research the biomechanical characteristics of human musculoskeletal system.
This dissertation is based on the key project“China mechanical virtual human”supported by National Natural Science Foundation. The object of this project is to develop a integrated computational platform for biomechanical analysis of human musculoskeletal system. This platform includes three modules, the 3D geometrical models and system integratation module, the human musculoskeletal system kinematics and kinetics analysis integration module, and the human musculoskeltal system finite element models and analysis integration module. To the integration problems in the project, the key technologies were studied and the integrated computational platform was developed. The main contents are listed as following:
1. Based on the human anatomical characteristics, the system integration of human musculoskeletal 3D geometrical models and simulation software package were developed. An integrated human musculoskeletal system is the base of the whole China mechanical virtual human project. First, a global coordinate system was developed according to the anatomics. The transformation between segmental local coordination and the global coordination were finished. Then, the anatomical kinematics of joints were defined. The muscle attachment positions to the skeletal system were measured, and muscles were modeled as force line to be assemblied into the human skeleton models. A human musculoskeletal 3D geometrical simulation software package was developed under Microsoft VisualStudio 2005 environment.
2. The integration of kinematics and kinetics analysis module were developed. Combining with NDI motion capture system, the human musculoskeletal motion capture and analysis module was developed, and was integrated with the human musculoskeletal kinetics analysis module.
3. A wavelet-based method was proposed to predict muscle forces from surface electromyography (EMG) signals in weightlifting motor task. EMG signals of biceps brachii, triceps brachii and deltoid muscles were recorded when subject did a standard weightlifting motor task. The wavelet-based algorithm was used to process raw EMG signals and extract features which could be input to the Hill-type muscle force models to predict muscle forces. Through comparison the results from the proposed method and conventional inverse dynamic computation method, the proposed method was validated. A component mode synthesis analysis method was also proposed and validated by femur modal analysis in a gait experiment.
4. Based on the parallel computing technology, the human musculoskeletal system integrated finite element model was built. According to the human joints characteristics, the finite element models of human joint system were built, include ankle joint, knee joint, hip joint and so on. The muscle forces were built as loads condition in the integrated finite element model.
5. Bending lift was chosed as the typical movement and the motion capture experiment was implemented. The motion process was devided as four static phases. The muscle forces were assigned as the loads condition. The ground reaction forces were assigned as the boundary condition and the stress distribution of whole human skeleton were analyzed. The parallel computing was finished on Dawning 4000A super computer platform in Shanghai Super Computing Center. Through testing of different parallel computing scheme, the best parallel computing platform was confirmed. The China mechanical virtual human integrated biomechanical computing platform was validated.
本文基于研究所承担的国家自然科学基金重点项目“中国力学虚拟人”,在中国可视人项目冷冻切片数据集的基础上,通过计算机虚拟技术、力学建模及分析技术、以及有限元建模及分析技术建立了一个人体骨肌系统生物力学计算平台。该平台主要包括人体骨肌系统的三维建模与系统集成模块、人体骨肌系统的运动学与动力学建模及系统集成模块、以及人体骨肌系统的有限元建模与系统集成模块等三大部分。重点针对中国力学虚拟人系统集成中的一些关键技术进行了研究,完成了力学虚拟人以上三大模块的系统集成开发,实现了力学虚拟人计算平台的功能。本文的主要工作可以归纳为以下几点:
1.基于人体解剖学特征结构,完成了中国力学虚拟人三维模型的系统集成和软件开发。一个完整的人体骨骼-肌肉模型是中国力学虚拟人课题的研究基础。为此,本文对由中国数字人冷冻切片数据库所建立起来的人体各部分模型进行了系统集成与软件开发。根据解剖学的要求,建立了虚拟人体整体坐标系统,对虚拟人各部分模型进行了坐标转换,对关节接触部分进行了解剖学运动关系的定义。根据肌肉力学虚拟线在骨骼上的附着位置,将肌肉力虚拟线模型装配在了虚拟人骨骼模型上,建立了能够反映真实人体骨肌系统解剖特性的三维模型。在Microsoft VisualStudio 2005环境下,开发了力学虚拟人三维模型仿真软件,实现了力学虚拟人三维几何模型的系统集成与仿真。
2.完成了中国力学虚拟人运动学与动力学模块的系统集成与开发。结合NDI运动捕捉系统,以基于人体测量学数据和特殊标记点(Marker)分布的算法,开发了力学虚拟人运动捕捉与分析模块,解决了该模块同运动捕捉硬件系统、动力学分析模块之间的数据接口问题。
3.对小波分析方法在人体骨肌系统EMG信号处理及肌肉力预测中的应用问题进行了探索性的研究。提出了一种基于小波理论的动态EMG信号预测肌肉力的方法。通过对举重运动员的举重动作进行运动捕捉实验、反向动力学建模以及分析,对肱二头肌、肱三头肌以及三角肌进行EMG信号测量,利用所提出的方法进行了肌肉力预测。经过对比,预测结果同反向动力学的预测结果相一致,验证了该方法的可用性。同时探索研究了利用模态综合方法来分析人体骨骼的振动特性和应变等问题,对人体步态进行了实验测量与分析,获得了较好的结果。
4.基于并行计算技术,建立了中国力学虚拟人系统集成有限元模型。根据人体关节联结的生理学和解剖学特性,对人体各部分的有限元模型进行系统集成建模。建立了踝关节、膝关节、髋关节、骶髂关节、肩关节、肘关节等部分的有限元连接模型,利用弹簧单元和连接单元对关节连接处的韧带和软骨进行了有限元建模。根据中国力学虚拟人骨肌系统三维整体模型,建立了有限元模型中的肌肉力载荷集,在下肢、上肢以及胸腰部分定义了肌肉力载荷集,用来模拟人体运动过程中,作用在骨骼上的肌肉力对骨骼系统应力分布的影响。
5.对人体的弯腰搬物动作进行了运动捕捉实验,将整个运动过程分为4个运动相位,建立了每个相位的有限元整体模型。基于运动学与动力学模块的分析计算结果,在上海超级计算中心的曙光4000A超级并行计算平台上,对人体弯腰搬物动作进行了整体有限元模型的仿真计算。针对本文所建立的人体骨肌系统总体有限元模型,对不同的并行计算方案进行了测试,确定了并行效率最佳的并行算法和硬件配置。通过对计算结果的比较分析,论证了中国力学虚拟人集成计算平台的可靠性。
Human musculoskeletal system is the requisite part for human movement in daily life. It is also fundamental for the interaction between human body with outside environment, and provide the subsistence for the organs. It is very important to research the biomechanical characteristics of human musculoskeletal system.
This dissertation is based on the key project“China mechanical virtual human”supported by National Natural Science Foundation. The object of this project is to develop a integrated computational platform for biomechanical analysis of human musculoskeletal system. This platform includes three modules, the 3D geometrical models and system integratation module, the human musculoskeletal system kinematics and kinetics analysis integration module, and the human musculoskeltal system finite element models and analysis integration module. To the integration problems in the project, the key technologies were studied and the integrated computational platform was developed. The main contents are listed as following:
1. Based on the human anatomical characteristics, the system integration of human musculoskeletal 3D geometrical models and simulation software package were developed. An integrated human musculoskeletal system is the base of the whole China mechanical virtual human project. First, a global coordinate system was developed according to the anatomics. The transformation between segmental local coordination and the global coordination were finished. Then, the anatomical kinematics of joints were defined. The muscle attachment positions to the skeletal system were measured, and muscles were modeled as force line to be assemblied into the human skeleton models. A human musculoskeletal 3D geometrical simulation software package was developed under Microsoft VisualStudio 2005 environment.
2. The integration of kinematics and kinetics analysis module were developed. Combining with NDI motion capture system, the human musculoskeletal motion capture and analysis module was developed, and was integrated with the human musculoskeletal kinetics analysis module.
3. A wavelet-based method was proposed to predict muscle forces from surface electromyography (EMG) signals in weightlifting motor task. EMG signals of biceps brachii, triceps brachii and deltoid muscles were recorded when subject did a standard weightlifting motor task. The wavelet-based algorithm was used to process raw EMG signals and extract features which could be input to the Hill-type muscle force models to predict muscle forces. Through comparison the results from the proposed method and conventional inverse dynamic computation method, the proposed method was validated. A component mode synthesis analysis method was also proposed and validated by femur modal analysis in a gait experiment.
4. Based on the parallel computing technology, the human musculoskeletal system integrated finite element model was built. According to the human joints characteristics, the finite element models of human joint system were built, include ankle joint, knee joint, hip joint and so on. The muscle forces were built as loads condition in the integrated finite element model.
5. Bending lift was chosed as the typical movement and the motion capture experiment was implemented. The motion process was devided as four static phases. The muscle forces were assigned as the loads condition. The ground reaction forces were assigned as the boundary condition and the stress distribution of whole human skeleton were analyzed. The parallel computing was finished on Dawning 4000A super computer platform in Shanghai Super Computing Center. Through testing of different parallel computing scheme, the best parallel computing platform was confirmed. The China mechanical virtual human integrated biomechanical computing platform was validated.
引文
1. Steven K. Boyd, Walter Herzog. Biomechanics of the Musculoskeletal System (3rd, editon). New York: Wiley Publishing Company
2.杨佳通.医用生物力学.1994,北京:科学出版社
3.冯元帧.生物力学.1983,北京:科学出版社
4. Nordin, M., & Frankel, V.H. (Eds). Basic Biomechanics of the Musculoskeletal System (2nd ed.). Philadelphia: Lea & Febiger.
5. Marco Viceconti, Debora Testi, Fulvia Taddei et. al. Biomechanics Modeling of the Musculoskeletal Apparatus: Status and Key Issues. Proceedings of The IEEE, 2006, 94(4):725-739
6. http://www.nlm.nih.gov/research/visible/visible_human.html
7. http://vkh3.kisti.re.kr/new/
8.林宗楷.中国数字化虚拟人体的科技问题.北京:香山科学会议第174次学术讨论会文集,2001,54-56
9. Ackennan M J. The Visible Human Project. Proceeding of IEEE, 1998,86:504-511
10. E. J. Crampin, M. Halstead, P. J. Hunter, P. M. F. Nielsen,D.Noble, N. P. Smith, and M. Tawhai. Computational Physiology and the Physiome Project. J. Exp. Physiol., 2004,89(1):1-26
11. E. Crampin, N. Smith, and P. Hunter. Multi-scale Modeling and the IUPS Physiome Project. J. Mol. Histol., 2004,35(7):707-714
12. P. J. Hunter and T. K. Borg. Integration from Proteins to Organs: The Physiome Project. Nature Rev. Mol. Cell Biol.,2003,4:237-243
13. G. Bock and J. A. Goode. Integrative Biological Modeling in Silico Simulation of Biological Processes. New York: Wiley,2002. 324-332
14. P. Kohl, D. Noble, R. L. Winslow, and P. J. Hunter.Computational Modeling of Biological System: Tools and visions. Phil. Trans. R. Soc. Lond. A, 2000, 358(7): 579-610
15. S. Brenner.“Biological computation,”in The Limits of Reductionism in Biology. New York: Wiley, 1998: 106-116
16. P. J. Hunter. The IUPS Physiome Project: A framework for computational physiology. Prog. Biophys. Mol. Biol, 2004,85(2):551-569
17. D. Noble. The Rise of Computational Biology. Nature Rev.Mol.Cell Biol., 2002, 3: 460-463
18. http://www.ndigital.com/
19. Miller. A Computer Simulation Model of the Airborne Phase of Diving. Pennsylvania: Pennsylvania State University. 1970
20. Passerello, Huston. Human Attitude Control. Journal of Biomechanics, 1971,4(2):95-102
21. Hatze. A Comprehensive Model for Human Motion Simulation and its Application to the Take-off Phase of the Long Jump. Journal of Biomechanics, 1981,14(3):135-142
22. Zajac. Muscle and Tendon: Properties, Models, Scaling, and Application to Biomechanics and Motor Control. Critical Review of Biomechanical Engineering, 1989, 17:359-411
23. Delp. Surgery Simulation: A Computer Graphics System to Analyze and Design Musculoskeletal Reconstructions of the Lower Limb. Stanford: Stanford University. 1990
24. http://www.musculographics.com/
25. http://www.anybodytech.com/
26. R.Davoodi, I.E.Brown, G.E.Loeb. Advanced modeling environment for developing and testing FES control systems. Medical Engineering and Physics, 2003, 25:3-9
27. Amy J. Simplifying Hill-based muscle models through generalized, extensible fuzzy heuristic implementation. Proceeding of SPIE, 2007, 12: 1-15
28.郑诚功.骨科生物力学的研究进展.中华创伤骨科杂志,2004,6(1):43-45
29. Hill, A. V. The heat of shortening and the dynamic constants of muscle. Proc. R. Soc. Lond. B 126, 136-195
30. Huxley, A. F. Muscle structure and theories of contraction. Prog. Biophysics and Biophysical Chemistry.1957, 7:255-318
31. Huxley, A.F.,Simmons,R.M.Proposed Mechanism of Force Generation in Straited Muscle. Nature,1971,233:533-538
32. Fung Y.C. Biomechanics:Mechanical Properties of Living Tissues, (2nd ed.), New York, Springer.
33. Heintz, S. and E.M. Gutierrez-Farewik, Static optimization of muscle forces during gait in comparison to EMG-to-force processing approach. Gait & Posture, 2007, 26(2): 279-288
34. Besier, D.G.L.a.T.F. An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. Journal of Biomechanics,2003,36:765-776
35. Thelen, D.G., F.C. Anderson, and S.L. Delp. Generating dynamic simulations of movement using computed muscle control. Journal of Biomechanics, 2003, 36(3): 321-328
36. Tamura, Y., M. Saito, and A. Ito, The phenomenological model of muscle contraction with a controller to simulate the excitation-contraction (E-C) coupling. Journal of Biomechanics, 2009, 42(3): 400-403
37. Pandy, A.S.a.M.G., A neuromusculoskeletal tracking method for estimating individual muscle forces in human movement. Journal of Biomechanics, 2007, 40:356-366
38. Huang, C.-Y. and W.Y. Gu, Effects of mechanical compression on metabolism and distribution of oxygen and lactate in intervertebral disc. Journal of Biomechanics, 2008, 41(6): 1184-1196
39.田心,毕平.生物力学基础.2006,北京:科学出版社
40. Carter DR. The compressive behavior of bone as a two-phase porous structure. JBJS. 1977:59(7): 954-962
41. Brekelmans WA, Poort HW, Slooff TJ. A new method to analyse the mechanical behaviour of skeletal parts. Acta Orthop Scand. 1972: 43(5):301-317
42. http://www.ulb.ac.be/project/vakhum/
43. C.Y. Tang , C.P.T., B. Stojanovic , M. Kojic, Finite element modelling of skeletal muscles coupled with fatigue. International Journal of Mechanical Sciences, 2007,49:1179-1191
44. Margareta Nordin, Victor H. Frankel著,郭适存,郭霞译.肌肉骨骼系统基础生物力学.2008,北京:人民卫生出版社
45.王海杰.人体系统解剖学(第三版).2008,上海:复旦大学出版社
46.张绍祥.可视化人体[EB]. http://www.chinesevisiblehuman.com/
47. SX Zhang, PA Heng, ZJ Liu, et al. The Chinese Visible Human (CVH) Datasets Incorporate Technical and Imaging Advances on Earlier Digital Humans [J]. J Anatomy, 2004, 204:165-173
48.施法中.计算机辅助几何设计与非均匀有理B样条(CAGD-NURBS).1994,北京:北京航空航天大学出版社.
49.罗述谦.数字化虚拟人图像处理及设想.中国数字化虚拟人体研究的发展与应用.北京:香山科学会议第208次学术讨论会文集,2003:18-22
50. Wu, G., et al., ISB recommendation on definitions of joint coordinate system of various joints for the reporting of human joint motion--part I: ankle, hip, and spine. Journal of Biomechanics, 2002. 35(4): 543-548.
51. Wu, G., et al., ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion--Part II: shoulder, elbow, wrist and hand. Journal of Biomechanics, 2005. 38(5): 981-992.
52. Cavanagh, G.W.a.P.R., ISB recommendations for standardization in the reporting of kinematic data. Journal of Biomechanics, 1995. 28(10): 1257-1261.
53. Hermens HJFB, Merletti R. European recommendation for surface electromyography. 1999, Netherlands:Roessingh Research and Development.
54. Crampin E., Smith N., Hunter P.. Multi-scale Modeling and the IUPS Physiome Project. Journal of Molecular Histology [J], 2004, 35(7): 707-714
55.钱学森.论人体科学[M].北京:人民军医出版社,1988.9-12
56.王超,张春秋,董心,刘海英.骨功能适应性数值模拟的若干进展.医用生物力学,2008,23(5):399-404
57.程亮,王冬梅,王成焘.骨重建数值仿真中的控制方程.医用生物力学,2007,22(4):417-422
58.王成焘.中国力学虚拟人.医用生物力学,2006,21(3):172-178
59. Ebb D, Tuttle RH, Baksh M. Pendular activity of human upper limbs during slow and normal walking. American Journal of Physical Anthropology, 1994, 93: 477–481
60. Teran, J., Creating and Simulating Skeletal Muscle from the Visible Human Data Set. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2005.
61. Pipeleers, G., et al., Dynamic simulation of human motion: numerically efficient inclusion of muscle physiology by convex optimization. Optimization and Engineering, 2008. 9(3): 213-238.
62. Liu, M.M., Dynamic muscle force predictions from EMG: an artificial neural network approach. Journal of Electromyography and Kinesiology, 1999.4: 103-107
63. Lester, W.T., A Neural Network Approach to Electromyographic Signal Processing for a Motor Control Task. Journal of Dynamic Systems, Measurement, and Control, 1997.
64. Heintz, S. and E.M. Gutierrez-Farewik, Static optimization of muscle forces during gait in comparison to EMG-to-force processing approach. Gait & Posture, 2007. 26(2): 279-288.
65. Gopura, R.A.R.C., EMG-Based Control of an Exoskeleton Robot for Human Forearm and Wrist Motion Assist. 2008 IEEE International Conference on Robotics and Automation, 2008.
66.崔锦泰.小波分析导论.西安:西安交通大学出版社,1997
67. Coorevits, P., et al., Test-retest reliability of wavelet - and Fourier based EMG (instantaneous)median frequencies in the evaluation of back and hip muscle fatigue during isometric back extensions. Journal of Electromyography and Kinesiology, 2008.18(5):798-806
68. DEBBAL, S.M., Filtering and classification of phonocardiogram signals using wavelet transform. Journal of Medical Engineering & Technology, 2008.32(1):53-65
69. Gaoxiang Ouyang, X.L., Yan Li, Xinping Guan, Application ofwavelet-based similarity analysis to epileptic seizures prediction. Computers in Biology and Medicine, 2007.37:430-437
70. Jiang Li, b.R.V.U., and Jianhua Yao, Wavelet method for CT colonography computer-aided polyp detection. Med. Phys, 2008.35(8):3527-3538
71. Paiva, J.P.L.M., et al., Adaptive wavelet EMG compression based on local optimization of filter banks. Physiological Measurement, 2008. 29(7): 843-856.
72. Stefan Karlsson a, B.r.G.b., c,*, Mean frequency and signal amplitude of the surface EMG of the quadriceps muscles increase with increasing torque—a study using the continuous wavelet transform. Journal of Electromyography and Kinesiology, 2001.11:131-140
73. Donald B.Percival.时间序列的小波方法(英文版).北京:机械工业出版社,2004.
74. Camilleri, M.J., Sloped muscle excitation waveforms improve the accuracy of forward dynamic simulations. Journal of Biomechanics, 2007.40:1423-1432
75. G.A.Lichtwark, A.M.Wilson. A modified Hill muscle model that predicts muscle power output and efficiency during sinusoidal length changes. The Journal of Experimental Biology, 2005,5:2831-2843
76. Hou, Y., et al., The Application of Neural Fuzzy Approaches to Modeling of Musculoskeletal Responses in Manual Lifting Tasks, in Fuzzy Applications in Industrial Engineering. 2006.5: 323-337.
77. Darryl G. Thelena, Frank C. Anderson, Using computed muscle control to generate forward dynamic simulations of human walking from experimental data. Journal of biomechanics, 2006,39:1107-1115
78. Potvin J.R., Norman R.W., McGill S.M. Mechanically corrected EMG for the continuous estimation of erector spinae muscle loading during repetitive lifting. European Journal of Applied Physiology and Occupational Physiology. 1996, 74(1):119-132
79. David G. Lloyd, Thor F. Besier. An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. Journal of biomechanics. 2003, 36:765-776
80. Langenderfer J., S. A. Jerabek, V. B. Thangamani, J. E. Kuhn, R. E. Hughes. Musculoskeletal parameters of muscles crossing the shoulder and elbow and the effect of sarcomere length sample size on estimation of optimal muscle length. Clinical Biomechanics. 2004, 19(7): 664-670.
81. Holzbaur K.R., Murray W.M., Delp S.L. A model of the upper extremity for simulating muscu-loskeletal surgery and analyzing neuromuscular control. Ann Biomed Eng. 2005, 33(6):829-840.
82. Buchler P, Ramaniraka NA, Rakotomanana LR, et al. A finite element model of the shoulder: Application to the comparison of normal and osteoarthritic joints. Clinical Biomechanics. 2002, 17(9): 630-639.
83. Merz B, Eckstein F, Hillebrand S, et al. Mechanical implications of humero-ulnarincongruity-Finite element analysis and experiment. Journal of Biomechanics. 1997,30(7): 713-721.
84. Buchler P, Farron A. Benefits of an anatomical reconstruction of the humeral head during shoulder arthroplasty: A finite element analysis. Clinical Biomechanics. 2004, 19(1): 16-23.
85. Maurel N, Diop A, Grimberg J. A 3D finite element model of an implanted scapula: Importance of a multiparametric validation using experimental data. Journal of Biomechanics. 2005, 38(9): 1865-1872.
86. Anderson AE, Peters CL, Tuttle BD, et al. Subject-specific finite element model of the pelvis: Development, validation and sensitivity studies. Journal of Biomechanical Engineering. 2005, 127(3):364-373.
87. Helgason B, Perilli E, Schileo E, et al. Mathematical relationships between bone density and mechanical properties: A literature review. Clinical Biomechanics. 2008, 23(2):135-146.
88.赵芳,周兴龙.人体材料力学.北京:北京体育大学出版社,1998.
89. Buchler P, Ramaniraka NA, Rakotomanana LR, et al. A finite element model of the shoulder: Application to the comparison of normal and osteoarthritic joints. Clinical Biomechanics. 2002, 17(9-10): 630-639.
90. Merz B, Eckstein F, Hillebrand S, et al. Mechanical implications of humero-ulnar incongruity - Finite element analysis and experiment. Journal of Biomechanics. 1997, 30(7):713-721.
91. Gibson LJ. The mechanical behaviour of cancellous bone. Journal of Biomechanics. 1985, 18(5): 317-328.
92. Helgason B, Perilli E, Schileo E, et al. Mathematical relationships between bone density and mechanical properties: A literature review. Clinical Biomechanics. 2008, 23(2): 135-146.
93. Buchler P, Farron A. Benefits of an anatomical reconstruction of the humeral head during shoulder arthroplasty: A finite element analysis. Clinical Biomechanics. 2004, 19(1): 16-23.
94. http://www.materialise.com/materialise/view/en/92458-Mimics.html
95. Schileo E, Taddei F, Malandrino A, et al. Subject-specific finite element models can accurately predict strain levels in long bones. Journal of Biomechanics. 2007, 40(13): 2982-2989.
96. Van Ee CA, Chasse AL, Myers BS. Quantifying skeletal muscle properties in cadaveric test specimens: Effects of mechanical loading, postmortem time, and freezer storage. Journal of Biomechanical Engineering. 2000, 122(1): 9-14.
97. Bovendeerd PHM, Arts T, Huyghe JM, et al. Dependence of local left ventricular wall mechanics on myocardial fiber orientation: A model study. Journal of Biomechanics. 1992, 25(10): 1129-1140.
98. Vankan WJ, Huyghe JM, Van Donkelaar CC, et al. Mechanical blood-tissue interaction in contracting muscles: A model study. Journal of Biomechanics. 1998, 31(5): 401-409.
99. Setton LA, Mow VC, Howell DS. Mechanical behavior of articular cartilage in shear is altered by transection of the anterior cruciate ligament. Journal of Orthopaedic Research. 1995, 13(4): 473-482.
100. Soltz MA, Ateshian GA. Experimental verification and theoretical prediction of cartilage interstitial fluid pressurization at an impermeable contact interface in confined compression.Journal of Biomechanics. 1998, 31(10): 927-934.
101. Flahiff CM, Kraus VB, Huebner JL, et al. Cartilage mechanics in the guinea pig model of osteoarthritis studied with an osmotic loading method. Osteoarthritis and Cartilage. 2004, 12(5): 383-388.
102. Hayes WC, Keer LM, Herrmann G, et al. Mathematical analysis for indentation tests of articular cartilage. Journal of Biomechanics. 1972, 5(5): 541-551.
103. Parsons JR, Black J. The viscoelastic shear behavior of normal rabbit articular cartilage. Journal of Biomechanics. 1977, 10(1): 21-29.
104. Mow VC, Kuei SC, Lai WM, et al. Biphasic creep and stress relaxation of articular cartilage in compression: Theory and experiments. Journal of Biomechanical Engineering. 1980, 102(1): 73-84.
105. Moore SM, McMahon PJ, Debski RE. Bi-directional Mechanical properties of the axillary pouch of the glenohumeral capsule: implications for modeling and surgical repair. Journal of Biomechanical Engineering. 2004, 126(2): 284-288.
106. Fung YC. Biomechanics: mechanical properties of living tissues. 2nd ed. New York:Springer-Verlag, 1993.
107. Pioletti DP, Rakotomanana LR, Leyvraz PF. Strain rate effect on the mechanical behavior of the anterior cruciate ligament-bone complex. Medical Engineering and Physics. 1999, 21(2): 95-100.
108. Pioletti DP, Rakotomanana LR, Benvenuti JF, et al. Viscoelastic constitutive law in large deformations: Application to human knee ligaments and tendons. Journal of Biomechanics. 1998, 31(8): 753-757.
109. Wilson AN, Frank CB, Shrive NG. Three dimensional model of the rabbit medical collateral ligament using the finite element method. in American Society of Mechanical Engineers, Petroleum Division (Publication) PD. 1994. London, Engl: Publ by ASME.
110. Gardiner JC, Weiss JA. Effects of flexion angle and valgus rotation on stresses in the human medial collateral ligament. American Society of Mechanical Engineers, Bioengineering Division (Publication) BED. 1997, 35: 27-28.
111. Weiss JA, Maker BN, Govindjee S. Finite element implementation of incompressible, transversely isotropic hyperelasticity. Computer Methods in Applied Mechanics and Engineering. 1996, 135(1): 107-128.
112. Debski RE, Weiss JA, Newman WJ, et al. Stress and strain in the anterior band of the inferior glenohumeral ligament during a simulated clinical examination. Journal of Shoulder and Elbow Surgery. 2005, 14(1 SUPPL.): 48-53
113. Rockwood, C.A. Jr. Dislocations about the shoulder. In C.A. Rockwood Jr. & D.P. Green(Eds.), Fractures (1st ed., Vol 1, pp.624-815). Philadelphia: J.B. Lippincott, 1975.
114. Itoi, E., Motzkin, N.E., Morrey, B.F., et al. Scapular inclination and inferior stability of the shoulder. J Shoulder Elbow Surg, 1992, 1: 131-139.
115. Morrey, B.F. Biomechanics of the elbow and forearm. In J.C. Delee & D. Drez (Eds.), Orthopaedic Sports Medicine (ch.17). Philadelphia: W.B. Saunders, 1994.
116.薛文,王坤正,凌伟.以三维有限元方法分析骨水泥填充成人股骨头坏死区域的力学变化.中国临床康复,2005,9(30):109-111
117. Burr, D.B., Milgrom, C., Fyhrie, D., Forwood, M., Nyska, M., Finestone, A., Hoshaw, S., Saiag, E. and Simkin, A., In vivo measurement of human tibial strains during vigorous activity. Bone, 1996, 18: 405–410.
118. Milgrom, C., Finestone, A., Simkin, A., Ekenman, I., Mendelson, S., Millgram, M., Nyska, M., Larsson, E. and Burr, D. In vivo strain measurements to evaluate the strengthening potential of exercises on the tibial bone. Journal of Bone and Joint Surgery, 2000,82: 591–594.
119. Milgrom, C., Radeva-Petrova, D.R., Finestone, A., Nyska, M., Mendelson, S., Benjuya, N., Simkin, A. and Burr, D. The effect of muscle fatigue on in vivo tibial strains. Journal of Biomechanics, 2006, 40: 845–850.
120. S K. Theories of musculoskeletal injury causation, Ergonomics. 2005, 44:17-47.
121. Fathallah FA, Marras WS, Parnianpour M. The role of complex, simultaneous trunk motions in the risk of occupation-related low back disorders. Spine. 1998, 23(9):1035-1042.
122. Bono CM. Low-Back Pain in Athletes. JBJS; 2004, 86: 382-396.
123. Mackerle J. Finite element modeling and simulations in orthopedics: a bibliography 1998-2005. Computer methods in biomechanics and biomedical engineering. 2006, 9(3):149-199.
124.同济大学数学教研室.高等数学第四版上册.高等教育出版社. 1996.
125. Seireg A, Arvikar RJ. A mathematical model for evaluation of forces in lower extremeties of the musculo skeletal system. Journal of Biomechanics. 1973, 6(3):313-326.
126. Buchanan T.S., Delp S.L., Solbeck J.A. Muscular resistance to varus and valgus loads at the elbow. Journal of Biomechanical Engineering. 1998, 120(5):634-639.
127. Frank C. Anderson, Marcus G. Pandy. Dynamic Optimization of Human Walking. Journal of Biomechanical Engineering. 2001, 123(10):381-390.
128.国家技术监督局.成年人体质心.中华人民共和国国家标准GB/T 17245-1998. 1998.
129. Crowninshield RD, Brand RA. A physiologically based criterion of muscle force prediction in locomotion. Journal of Biomechanics. 1981, 14(11):793-801.
130. Pedotti A, Krishnan VV, Stark L. Optimization of muscle-force sequencing in human locomotion. Mathematical Biosciences. 1978, 38(1-2):57-76.
131. Granata KP, Marras WS. An EMG-assisted model of loads on the lumbar spine during asymmetric trunk extensions. Journal of Biomechanics. 1993, 26(12): 1429-1438.
132. McGill SM. Electromyographic activity of the abdominal and low back musculature during the generation of isometric and dynamic axial trunk torque: Implications for lumbar mechanics. Journal of Orthopaedic Research. 1991, 9(1):91-103.
133.王启平、王璐、伍毅等.结构高性能计算中的并行有限元方法.安徽工业大学学报,2005,22(2):135-138.
134.聂文忠.脊柱胸腰部的生物力学建模与应用研究—中国力学虚拟人的基本问题初探.上海交通大学博士学位论文,上海,2009.
135. Van Dieen, J.H., Hoozemans, M.J.M., Toussaint, H.M. Stoop or squat: A review of biomechanical studies of lifting techniques. Clin Biomechanics, 1999, 14(3): 685-691.
2.杨佳通.医用生物力学.1994,北京:科学出版社
3.冯元帧.生物力学.1983,北京:科学出版社
4. Nordin, M., & Frankel, V.H. (Eds). Basic Biomechanics of the Musculoskeletal System (2nd ed.). Philadelphia: Lea & Febiger.
5. Marco Viceconti, Debora Testi, Fulvia Taddei et. al. Biomechanics Modeling of the Musculoskeletal Apparatus: Status and Key Issues. Proceedings of The IEEE, 2006, 94(4):725-739
6. http://www.nlm.nih.gov/research/visible/visible_human.html
7. http://vkh3.kisti.re.kr/new/
8.林宗楷.中国数字化虚拟人体的科技问题.北京:香山科学会议第174次学术讨论会文集,2001,54-56
9. Ackennan M J. The Visible Human Project. Proceeding of IEEE, 1998,86:504-511
10. E. J. Crampin, M. Halstead, P. J. Hunter, P. M. F. Nielsen,D.Noble, N. P. Smith, and M. Tawhai. Computational Physiology and the Physiome Project. J. Exp. Physiol., 2004,89(1):1-26
11. E. Crampin, N. Smith, and P. Hunter. Multi-scale Modeling and the IUPS Physiome Project. J. Mol. Histol., 2004,35(7):707-714
12. P. J. Hunter and T. K. Borg. Integration from Proteins to Organs: The Physiome Project. Nature Rev. Mol. Cell Biol.,2003,4:237-243
13. G. Bock and J. A. Goode. Integrative Biological Modeling in Silico Simulation of Biological Processes. New York: Wiley,2002. 324-332
14. P. Kohl, D. Noble, R. L. Winslow, and P. J. Hunter.Computational Modeling of Biological System: Tools and visions. Phil. Trans. R. Soc. Lond. A, 2000, 358(7): 579-610
15. S. Brenner.“Biological computation,”in The Limits of Reductionism in Biology. New York: Wiley, 1998: 106-116
16. P. J. Hunter. The IUPS Physiome Project: A framework for computational physiology. Prog. Biophys. Mol. Biol, 2004,85(2):551-569
17. D. Noble. The Rise of Computational Biology. Nature Rev.Mol.Cell Biol., 2002, 3: 460-463
18. http://www.ndigital.com/
19. Miller. A Computer Simulation Model of the Airborne Phase of Diving. Pennsylvania: Pennsylvania State University. 1970
20. Passerello, Huston. Human Attitude Control. Journal of Biomechanics, 1971,4(2):95-102
21. Hatze. A Comprehensive Model for Human Motion Simulation and its Application to the Take-off Phase of the Long Jump. Journal of Biomechanics, 1981,14(3):135-142
22. Zajac. Muscle and Tendon: Properties, Models, Scaling, and Application to Biomechanics and Motor Control. Critical Review of Biomechanical Engineering, 1989, 17:359-411
23. Delp. Surgery Simulation: A Computer Graphics System to Analyze and Design Musculoskeletal Reconstructions of the Lower Limb. Stanford: Stanford University. 1990
24. http://www.musculographics.com/
25. http://www.anybodytech.com/
26. R.Davoodi, I.E.Brown, G.E.Loeb. Advanced modeling environment for developing and testing FES control systems. Medical Engineering and Physics, 2003, 25:3-9
27. Amy J. Simplifying Hill-based muscle models through generalized, extensible fuzzy heuristic implementation. Proceeding of SPIE, 2007, 12: 1-15
28.郑诚功.骨科生物力学的研究进展.中华创伤骨科杂志,2004,6(1):43-45
29. Hill, A. V. The heat of shortening and the dynamic constants of muscle. Proc. R. Soc. Lond. B 126, 136-195
30. Huxley, A. F. Muscle structure and theories of contraction. Prog. Biophysics and Biophysical Chemistry.1957, 7:255-318
31. Huxley, A.F.,Simmons,R.M.Proposed Mechanism of Force Generation in Straited Muscle. Nature,1971,233:533-538
32. Fung Y.C. Biomechanics:Mechanical Properties of Living Tissues, (2nd ed.), New York, Springer.
33. Heintz, S. and E.M. Gutierrez-Farewik, Static optimization of muscle forces during gait in comparison to EMG-to-force processing approach. Gait & Posture, 2007, 26(2): 279-288
34. Besier, D.G.L.a.T.F. An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. Journal of Biomechanics,2003,36:765-776
35. Thelen, D.G., F.C. Anderson, and S.L. Delp. Generating dynamic simulations of movement using computed muscle control. Journal of Biomechanics, 2003, 36(3): 321-328
36. Tamura, Y., M. Saito, and A. Ito, The phenomenological model of muscle contraction with a controller to simulate the excitation-contraction (E-C) coupling. Journal of Biomechanics, 2009, 42(3): 400-403
37. Pandy, A.S.a.M.G., A neuromusculoskeletal tracking method for estimating individual muscle forces in human movement. Journal of Biomechanics, 2007, 40:356-366
38. Huang, C.-Y. and W.Y. Gu, Effects of mechanical compression on metabolism and distribution of oxygen and lactate in intervertebral disc. Journal of Biomechanics, 2008, 41(6): 1184-1196
39.田心,毕平.生物力学基础.2006,北京:科学出版社
40. Carter DR. The compressive behavior of bone as a two-phase porous structure. JBJS. 1977:59(7): 954-962
41. Brekelmans WA, Poort HW, Slooff TJ. A new method to analyse the mechanical behaviour of skeletal parts. Acta Orthop Scand. 1972: 43(5):301-317
42. http://www.ulb.ac.be/project/vakhum/
43. C.Y. Tang , C.P.T., B. Stojanovic , M. Kojic, Finite element modelling of skeletal muscles coupled with fatigue. International Journal of Mechanical Sciences, 2007,49:1179-1191
44. Margareta Nordin, Victor H. Frankel著,郭适存,郭霞译.肌肉骨骼系统基础生物力学.2008,北京:人民卫生出版社
45.王海杰.人体系统解剖学(第三版).2008,上海:复旦大学出版社
46.张绍祥.可视化人体[EB]. http://www.chinesevisiblehuman.com/
47. SX Zhang, PA Heng, ZJ Liu, et al. The Chinese Visible Human (CVH) Datasets Incorporate Technical and Imaging Advances on Earlier Digital Humans [J]. J Anatomy, 2004, 204:165-173
48.施法中.计算机辅助几何设计与非均匀有理B样条(CAGD-NURBS).1994,北京:北京航空航天大学出版社.
49.罗述谦.数字化虚拟人图像处理及设想.中国数字化虚拟人体研究的发展与应用.北京:香山科学会议第208次学术讨论会文集,2003:18-22
50. Wu, G., et al., ISB recommendation on definitions of joint coordinate system of various joints for the reporting of human joint motion--part I: ankle, hip, and spine. Journal of Biomechanics, 2002. 35(4): 543-548.
51. Wu, G., et al., ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion--Part II: shoulder, elbow, wrist and hand. Journal of Biomechanics, 2005. 38(5): 981-992.
52. Cavanagh, G.W.a.P.R., ISB recommendations for standardization in the reporting of kinematic data. Journal of Biomechanics, 1995. 28(10): 1257-1261.
53. Hermens HJFB, Merletti R. European recommendation for surface electromyography. 1999, Netherlands:Roessingh Research and Development.
54. Crampin E., Smith N., Hunter P.. Multi-scale Modeling and the IUPS Physiome Project. Journal of Molecular Histology [J], 2004, 35(7): 707-714
55.钱学森.论人体科学[M].北京:人民军医出版社,1988.9-12
56.王超,张春秋,董心,刘海英.骨功能适应性数值模拟的若干进展.医用生物力学,2008,23(5):399-404
57.程亮,王冬梅,王成焘.骨重建数值仿真中的控制方程.医用生物力学,2007,22(4):417-422
58.王成焘.中国力学虚拟人.医用生物力学,2006,21(3):172-178
59. Ebb D, Tuttle RH, Baksh M. Pendular activity of human upper limbs during slow and normal walking. American Journal of Physical Anthropology, 1994, 93: 477–481
60. Teran, J., Creating and Simulating Skeletal Muscle from the Visible Human Data Set. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2005.
61. Pipeleers, G., et al., Dynamic simulation of human motion: numerically efficient inclusion of muscle physiology by convex optimization. Optimization and Engineering, 2008. 9(3): 213-238.
62. Liu, M.M., Dynamic muscle force predictions from EMG: an artificial neural network approach. Journal of Electromyography and Kinesiology, 1999.4: 103-107
63. Lester, W.T., A Neural Network Approach to Electromyographic Signal Processing for a Motor Control Task. Journal of Dynamic Systems, Measurement, and Control, 1997.
64. Heintz, S. and E.M. Gutierrez-Farewik, Static optimization of muscle forces during gait in comparison to EMG-to-force processing approach. Gait & Posture, 2007. 26(2): 279-288.
65. Gopura, R.A.R.C., EMG-Based Control of an Exoskeleton Robot for Human Forearm and Wrist Motion Assist. 2008 IEEE International Conference on Robotics and Automation, 2008.
66.崔锦泰.小波分析导论.西安:西安交通大学出版社,1997
67. Coorevits, P., et al., Test-retest reliability of wavelet - and Fourier based EMG (instantaneous)median frequencies in the evaluation of back and hip muscle fatigue during isometric back extensions. Journal of Electromyography and Kinesiology, 2008.18(5):798-806
68. DEBBAL, S.M., Filtering and classification of phonocardiogram signals using wavelet transform. Journal of Medical Engineering & Technology, 2008.32(1):53-65
69. Gaoxiang Ouyang, X.L., Yan Li, Xinping Guan, Application ofwavelet-based similarity analysis to epileptic seizures prediction. Computers in Biology and Medicine, 2007.37:430-437
70. Jiang Li, b.R.V.U., and Jianhua Yao, Wavelet method for CT colonography computer-aided polyp detection. Med. Phys, 2008.35(8):3527-3538
71. Paiva, J.P.L.M., et al., Adaptive wavelet EMG compression based on local optimization of filter banks. Physiological Measurement, 2008. 29(7): 843-856.
72. Stefan Karlsson a, B.r.G.b., c,*, Mean frequency and signal amplitude of the surface EMG of the quadriceps muscles increase with increasing torque—a study using the continuous wavelet transform. Journal of Electromyography and Kinesiology, 2001.11:131-140
73. Donald B.Percival.时间序列的小波方法(英文版).北京:机械工业出版社,2004.
74. Camilleri, M.J., Sloped muscle excitation waveforms improve the accuracy of forward dynamic simulations. Journal of Biomechanics, 2007.40:1423-1432
75. G.A.Lichtwark, A.M.Wilson. A modified Hill muscle model that predicts muscle power output and efficiency during sinusoidal length changes. The Journal of Experimental Biology, 2005,5:2831-2843
76. Hou, Y., et al., The Application of Neural Fuzzy Approaches to Modeling of Musculoskeletal Responses in Manual Lifting Tasks, in Fuzzy Applications in Industrial Engineering. 2006.5: 323-337.
77. Darryl G. Thelena, Frank C. Anderson, Using computed muscle control to generate forward dynamic simulations of human walking from experimental data. Journal of biomechanics, 2006,39:1107-1115
78. Potvin J.R., Norman R.W., McGill S.M. Mechanically corrected EMG for the continuous estimation of erector spinae muscle loading during repetitive lifting. European Journal of Applied Physiology and Occupational Physiology. 1996, 74(1):119-132
79. David G. Lloyd, Thor F. Besier. An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. Journal of biomechanics. 2003, 36:765-776
80. Langenderfer J., S. A. Jerabek, V. B. Thangamani, J. E. Kuhn, R. E. Hughes. Musculoskeletal parameters of muscles crossing the shoulder and elbow and the effect of sarcomere length sample size on estimation of optimal muscle length. Clinical Biomechanics. 2004, 19(7): 664-670.
81. Holzbaur K.R., Murray W.M., Delp S.L. A model of the upper extremity for simulating muscu-loskeletal surgery and analyzing neuromuscular control. Ann Biomed Eng. 2005, 33(6):829-840.
82. Buchler P, Ramaniraka NA, Rakotomanana LR, et al. A finite element model of the shoulder: Application to the comparison of normal and osteoarthritic joints. Clinical Biomechanics. 2002, 17(9): 630-639.
83. Merz B, Eckstein F, Hillebrand S, et al. Mechanical implications of humero-ulnarincongruity-Finite element analysis and experiment. Journal of Biomechanics. 1997,30(7): 713-721.
84. Buchler P, Farron A. Benefits of an anatomical reconstruction of the humeral head during shoulder arthroplasty: A finite element analysis. Clinical Biomechanics. 2004, 19(1): 16-23.
85. Maurel N, Diop A, Grimberg J. A 3D finite element model of an implanted scapula: Importance of a multiparametric validation using experimental data. Journal of Biomechanics. 2005, 38(9): 1865-1872.
86. Anderson AE, Peters CL, Tuttle BD, et al. Subject-specific finite element model of the pelvis: Development, validation and sensitivity studies. Journal of Biomechanical Engineering. 2005, 127(3):364-373.
87. Helgason B, Perilli E, Schileo E, et al. Mathematical relationships between bone density and mechanical properties: A literature review. Clinical Biomechanics. 2008, 23(2):135-146.
88.赵芳,周兴龙.人体材料力学.北京:北京体育大学出版社,1998.
89. Buchler P, Ramaniraka NA, Rakotomanana LR, et al. A finite element model of the shoulder: Application to the comparison of normal and osteoarthritic joints. Clinical Biomechanics. 2002, 17(9-10): 630-639.
90. Merz B, Eckstein F, Hillebrand S, et al. Mechanical implications of humero-ulnar incongruity - Finite element analysis and experiment. Journal of Biomechanics. 1997, 30(7):713-721.
91. Gibson LJ. The mechanical behaviour of cancellous bone. Journal of Biomechanics. 1985, 18(5): 317-328.
92. Helgason B, Perilli E, Schileo E, et al. Mathematical relationships between bone density and mechanical properties: A literature review. Clinical Biomechanics. 2008, 23(2): 135-146.
93. Buchler P, Farron A. Benefits of an anatomical reconstruction of the humeral head during shoulder arthroplasty: A finite element analysis. Clinical Biomechanics. 2004, 19(1): 16-23.
94. http://www.materialise.com/materialise/view/en/92458-Mimics.html
95. Schileo E, Taddei F, Malandrino A, et al. Subject-specific finite element models can accurately predict strain levels in long bones. Journal of Biomechanics. 2007, 40(13): 2982-2989.
96. Van Ee CA, Chasse AL, Myers BS. Quantifying skeletal muscle properties in cadaveric test specimens: Effects of mechanical loading, postmortem time, and freezer storage. Journal of Biomechanical Engineering. 2000, 122(1): 9-14.
97. Bovendeerd PHM, Arts T, Huyghe JM, et al. Dependence of local left ventricular wall mechanics on myocardial fiber orientation: A model study. Journal of Biomechanics. 1992, 25(10): 1129-1140.
98. Vankan WJ, Huyghe JM, Van Donkelaar CC, et al. Mechanical blood-tissue interaction in contracting muscles: A model study. Journal of Biomechanics. 1998, 31(5): 401-409.
99. Setton LA, Mow VC, Howell DS. Mechanical behavior of articular cartilage in shear is altered by transection of the anterior cruciate ligament. Journal of Orthopaedic Research. 1995, 13(4): 473-482.
100. Soltz MA, Ateshian GA. Experimental verification and theoretical prediction of cartilage interstitial fluid pressurization at an impermeable contact interface in confined compression.Journal of Biomechanics. 1998, 31(10): 927-934.
101. Flahiff CM, Kraus VB, Huebner JL, et al. Cartilage mechanics in the guinea pig model of osteoarthritis studied with an osmotic loading method. Osteoarthritis and Cartilage. 2004, 12(5): 383-388.
102. Hayes WC, Keer LM, Herrmann G, et al. Mathematical analysis for indentation tests of articular cartilage. Journal of Biomechanics. 1972, 5(5): 541-551.
103. Parsons JR, Black J. The viscoelastic shear behavior of normal rabbit articular cartilage. Journal of Biomechanics. 1977, 10(1): 21-29.
104. Mow VC, Kuei SC, Lai WM, et al. Biphasic creep and stress relaxation of articular cartilage in compression: Theory and experiments. Journal of Biomechanical Engineering. 1980, 102(1): 73-84.
105. Moore SM, McMahon PJ, Debski RE. Bi-directional Mechanical properties of the axillary pouch of the glenohumeral capsule: implications for modeling and surgical repair. Journal of Biomechanical Engineering. 2004, 126(2): 284-288.
106. Fung YC. Biomechanics: mechanical properties of living tissues. 2nd ed. New York:Springer-Verlag, 1993.
107. Pioletti DP, Rakotomanana LR, Leyvraz PF. Strain rate effect on the mechanical behavior of the anterior cruciate ligament-bone complex. Medical Engineering and Physics. 1999, 21(2): 95-100.
108. Pioletti DP, Rakotomanana LR, Benvenuti JF, et al. Viscoelastic constitutive law in large deformations: Application to human knee ligaments and tendons. Journal of Biomechanics. 1998, 31(8): 753-757.
109. Wilson AN, Frank CB, Shrive NG. Three dimensional model of the rabbit medical collateral ligament using the finite element method. in American Society of Mechanical Engineers, Petroleum Division (Publication) PD. 1994. London, Engl: Publ by ASME.
110. Gardiner JC, Weiss JA. Effects of flexion angle and valgus rotation on stresses in the human medial collateral ligament. American Society of Mechanical Engineers, Bioengineering Division (Publication) BED. 1997, 35: 27-28.
111. Weiss JA, Maker BN, Govindjee S. Finite element implementation of incompressible, transversely isotropic hyperelasticity. Computer Methods in Applied Mechanics and Engineering. 1996, 135(1): 107-128.
112. Debski RE, Weiss JA, Newman WJ, et al. Stress and strain in the anterior band of the inferior glenohumeral ligament during a simulated clinical examination. Journal of Shoulder and Elbow Surgery. 2005, 14(1 SUPPL.): 48-53
113. Rockwood, C.A. Jr. Dislocations about the shoulder. In C.A. Rockwood Jr. & D.P. Green(Eds.), Fractures (1st ed., Vol 1, pp.624-815). Philadelphia: J.B. Lippincott, 1975.
114. Itoi, E., Motzkin, N.E., Morrey, B.F., et al. Scapular inclination and inferior stability of the shoulder. J Shoulder Elbow Surg, 1992, 1: 131-139.
115. Morrey, B.F. Biomechanics of the elbow and forearm. In J.C. Delee & D. Drez (Eds.), Orthopaedic Sports Medicine (ch.17). Philadelphia: W.B. Saunders, 1994.
116.薛文,王坤正,凌伟.以三维有限元方法分析骨水泥填充成人股骨头坏死区域的力学变化.中国临床康复,2005,9(30):109-111
117. Burr, D.B., Milgrom, C., Fyhrie, D., Forwood, M., Nyska, M., Finestone, A., Hoshaw, S., Saiag, E. and Simkin, A., In vivo measurement of human tibial strains during vigorous activity. Bone, 1996, 18: 405–410.
118. Milgrom, C., Finestone, A., Simkin, A., Ekenman, I., Mendelson, S., Millgram, M., Nyska, M., Larsson, E. and Burr, D. In vivo strain measurements to evaluate the strengthening potential of exercises on the tibial bone. Journal of Bone and Joint Surgery, 2000,82: 591–594.
119. Milgrom, C., Radeva-Petrova, D.R., Finestone, A., Nyska, M., Mendelson, S., Benjuya, N., Simkin, A. and Burr, D. The effect of muscle fatigue on in vivo tibial strains. Journal of Biomechanics, 2006, 40: 845–850.
120. S K. Theories of musculoskeletal injury causation, Ergonomics. 2005, 44:17-47.
121. Fathallah FA, Marras WS, Parnianpour M. The role of complex, simultaneous trunk motions in the risk of occupation-related low back disorders. Spine. 1998, 23(9):1035-1042.
122. Bono CM. Low-Back Pain in Athletes. JBJS; 2004, 86: 382-396.
123. Mackerle J. Finite element modeling and simulations in orthopedics: a bibliography 1998-2005. Computer methods in biomechanics and biomedical engineering. 2006, 9(3):149-199.
124.同济大学数学教研室.高等数学第四版上册.高等教育出版社. 1996.
125. Seireg A, Arvikar RJ. A mathematical model for evaluation of forces in lower extremeties of the musculo skeletal system. Journal of Biomechanics. 1973, 6(3):313-326.
126. Buchanan T.S., Delp S.L., Solbeck J.A. Muscular resistance to varus and valgus loads at the elbow. Journal of Biomechanical Engineering. 1998, 120(5):634-639.
127. Frank C. Anderson, Marcus G. Pandy. Dynamic Optimization of Human Walking. Journal of Biomechanical Engineering. 2001, 123(10):381-390.
128.国家技术监督局.成年人体质心.中华人民共和国国家标准GB/T 17245-1998. 1998.
129. Crowninshield RD, Brand RA. A physiologically based criterion of muscle force prediction in locomotion. Journal of Biomechanics. 1981, 14(11):793-801.
130. Pedotti A, Krishnan VV, Stark L. Optimization of muscle-force sequencing in human locomotion. Mathematical Biosciences. 1978, 38(1-2):57-76.
131. Granata KP, Marras WS. An EMG-assisted model of loads on the lumbar spine during asymmetric trunk extensions. Journal of Biomechanics. 1993, 26(12): 1429-1438.
132. McGill SM. Electromyographic activity of the abdominal and low back musculature during the generation of isometric and dynamic axial trunk torque: Implications for lumbar mechanics. Journal of Orthopaedic Research. 1991, 9(1):91-103.
133.王启平、王璐、伍毅等.结构高性能计算中的并行有限元方法.安徽工业大学学报,2005,22(2):135-138.
134.聂文忠.脊柱胸腰部的生物力学建模与应用研究—中国力学虚拟人的基本问题初探.上海交通大学博士学位论文,上海,2009.
135. Van Dieen, J.H., Hoozemans, M.J.M., Toussaint, H.M. Stoop or squat: A review of biomechanical studies of lifting techniques. Clin Biomechanics, 1999, 14(3): 685-691.