[1]SHAO Mingxu,WANG Fei,YIN Tenglong,et al.Research progress on the human lower limb biomechanical modeling[J].CAAI Transactions on Intelligent Systems,2015,10(4):518-527.[doi:10.3969/j.issn.1673-4785.201503039]
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Research progress on the human lower limb biomechanical modeling

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 10 Number of periods: 2015 4 Page number: 518-527 Column: 综述 Public date: 2015-08-25
Title:
Research progress on the human lower limb biomechanical modeling
Author(s):
SHAO Mingxu;  WANG Fei;  YIN Tenglong;  LIU Jian
College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
Keywords:
biomechanical modeling of human lower limb; Lagrange equation; theorem of angular momentum; Hill model; simulation software modeling; black box training modeling
CLC:
TP391
DOI:
10.3969/j.issn.1673-4785.201503039
Abstract:
The research on the biomechanical modeling and simulation of human lower limbs is an important content in the development of wearable exoskeleton robots. Theoretical and technical methods derived from this research can promote the process of biomechanics, rehabilitation medicine and prosthetic/orthotic devices. This work reviews the state-of-the-art techniques for modeling and simulating biomechanics of human lower limbs and makes analysis of popular methods, such as multi-body modeling, simulation software modeling, Hill three elements modeling and black box training modeling based on Lagrange equation and theorem of angular momentum. The future prospects in this research field are also provided in this paper. The biomechanical modeling and simulating methods discussed is of great significance to the design of naturally harmonious human-robot interaction of wearable exoskeleton robots.
References:
[1] DOLLAR A M, HERR H. Lower extremity exoskeletons and active orthoses: challenges and state-of-the-art[J]. IEEE Transactions on Robotics, 2008, 24(1): 144-158.
[2] 吕厚山. 人工关节外科学[M]. 北京: 科学出版社, 2001: 1-799. LYU Houshan. Artificial Joint Surgery[M]. Beijing: Science Press, 2001: 1-799.
[3] MOEINZADEH M H, ENGIN A E, AKKAS N. Two-dimensional dynamic modeling of human knee joint[J]. Journal of Biomechanics, 1983, 16(4): 253-264.
[4] ROYER T, KOENIG M. Joint loading and bone mineral density in persons with unilateral, trans-tibial amputation[J]. Clinical Biomechanics, 2005, 20(10): 1119-1125.
[5] YANG C J, ZHANG J F, CHEN Y, et al. A review of exoskeleton-type systems and their key technologies[J]. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2008, 222(8): 1599-1612.
[6] KAZEROONI H. Human augmentation and exoskeleton systems in Berkeley[J]. International Journal of Humanoid Robotics, 2007, 4(3): 575-605.
[7] BRAND R A. The biomechanics and motor control of human gait: normal, elderly, and pathological[M]. Waterloo: University of Waterloo Press, 1991: 14-15, 1-384.
[8] TUMER S T, ENGIN A E. Three-body segment dynamic model of the human knee[J]. Journal of Biomechanical Engineering, 1993, 115(4A): 350-356.
[9] MOEINZADEH M H, ENGIN A E, AKKAS N. Two-dimensional dynamic modeling of human knee joint[J]. Journal of Biomechanics, 1982, 15(4): 346.
[10] AYOUB M M. A 2-D simulation model for lifting activities[J]. Computers & Industrial Engineering, 1998, 35(3-4): 619-622.
[11] PANDY M G, ZAJAC F E, SIM E, et al. An optimal control model for maximum-height human jumping[J]. Journal of Biomechanics, 1990, 23(12): 1185-1198.
[12] SP?GELE T, KISTNER A, GOLLHOFER A. Modelling, simulation and optimisation of a human vertical jump[J]. Journal of Biomechanics, 1999, 32(5): 521-530.
[13] Anolg Devices, Inc. ADXL203 Data Sheet[DB/OL]. [2006-04-27]. http://www.analog.com/UploadedFiles/Data_Sheets/ADXL103_203.pdf.
[14] FAN Yuanjie, YIN Yuehong. Active and progressive exoskeleton rehabilitation using multisource information fusion from EMG and force-position EPP[J]. IEEE Transactions on Biomedical Engineering, 2013, 60(12): 3314-3321.
[15] HANAVAN E P. A mathematical model of the human body.AD608463[R] [S.l.], 1964.
[16] BLAJER W, CZAPLICKI A. Modeling and inverse simulation of somersaults on the trampoline[J]. Journal of Biomechanics, 2001, 34(12): 1619-1629.
[17] ANDERSON F C, PANDY M G. Dynamic optimization of human walking[J]. Journal of Biomechanical Engineering, 2001, 123(5): 381-390.
[18] PEJHAN S, FARAHMAND F, PARNIANPOUR M. Design optimization of an above-knee prosthesis based on the kinematics of gait[C]//30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vancouver, Canada, 2008: 4274-4277.
[19] 张国伟,宋伟刚.并联机器人动力学问题的Kane方法[J].系统仿真学报, 2004, 16(7): 1386-1391. ZHANG Guowei, SONG Weigang. A Kane formulation for the inverse dynamic of Stewart platform manipulator[J]. Journal of System Simulation, 2004, 16(7): 1386-1391.
[20] 刘延斌, 韩秀英,薛玉君,等.3-RRRT并联机器人动力学仿真[J].系统仿真学报, 2006, 18(7): 1962-1965. LIU Yanbin, HAN Xiuying, XUE Yujun, et al. Dynamics simulation of a 3-RRRT parallel robot[J]. Journal of System Simulation, 2006, 18(7): 1962-1965.
[21] TIBERT G. Deployable tenegrity structures for space application[R].Stockholm: Royal Institute of Technology, 2002.
[22] JENKYN T R, NICOL A C. A multi-segment kinematic model of the foot with a novel definition of forefoot motion for use in clinical gait analysis during walking[J]. Journal of Biomechanics, 2007, 40(14): 3271-3278.
[23] SMITH S L. Application of high-speed videography in sports analysis[C]//Proceedings of SPIE 1757, Ultrahigh- and High-Speed Photography, Videography, and Photonics. San Diego, USA, 1992: 118.
[24] NARUSE K, KAWAI S, KUKICHI T. Three-dimensional lifting-up motion analysis for wearable power assist device of lower back support[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems. Edmonton, Canada, 2005: 2959-2964.
[25] KIGUCHI K, HAYASHI Y. Estimation of joint torque for a myoelectric arm by genetic programming based on EMG signals[C]//IEEE World Automation Congress (WAC). Puerto Vallarta, Mexico, 2012: 1-4.
[26] SARTORI M, REGGIANI M, PAGELLO E, et al. Modeling the human knee for assistive technologies[J]. IEEE Transactions on Biomedical Engineering, 2012, 59(9): 2642-2649.
[27] PATRINOS P, ALEXANDRIDIS A, NINOS K, et al. Variable selection in nonlinear modeling based on RBF networks and evolutionary computation[J]. International Journal of Neural Systems, 2010, 20(5): 365-379.
[28] SONG R, TONG K Y. Using recurrent artificial neural network model to estimate voluntary elbow torque in dynamic situations[J]. Medical and Biological Engineering and Computing, 2005, 43(4): 473-480.
[29] 金德闻,王人成,白彩勤. 电流变液智能下肢假肢摆动相控制原理与方法[J].清华大学学报:自然科学版, 1998, 38(2): 40-43. JIN Dewen, WANG Rencheng, BAI Caiqin. Swing phase control of intelligent lower limb prosthesis using electrorheological fluid[J]. Journal of Tsinghua University: Science and Technology, 1998, 38(2): 40-43.
[30] MARTINEZ-VILLALPANDO E C, MOONEY L, ELLIOTT G, et al. Antagonistic active knee prosthesis. A metabolic cost of walking comparison with a variable-damping prosthetic knee[C]//Proceedings of the 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Boston, USA, 2011: 8519-8522.
[31] 王斌锐,金英连,徐心和.仿生膝关节虚拟样机与协同仿真方法研究[J].系统仿真学报, 2006, 18(6): 1554-1557. WANG Binrui, JIN Yinglian, XU Xinhe. Virtual prototype and collaborative simulation of bionic knee joint[J]. Journal of System Simulation, 2006, 18(6): 1554-1557.
[32] 朱昌义. 单杠上人体摆动的凯恩动力学模型[J]. 成都体育学院学报, 2000, 26(6): 71-74. ZHU Changyi. Kaine dynamics model of human swing on the horizontal bar[J]. Journal of Chengdu Sport University, 2000, 26(6): 71-74.
[33] 刘明辉, 顾文锦, 陈占伏. 基于骨骼服的虚拟人体建模与仿真[J]. 海军航空工程学院学报, 2009, 24(2): 157-161. LIU Minghui, GU Wenjin, CHEN Zhanfu. Virtual human body modeling and simulation based on skeletal services[J]. Journal of Naval Aeronautical and Astronautical University, 2009, 24(2): 157-161.
[34] 沈凌, 孟青云, 喻洪流. 基于虚拟样机技术的下肢假肢结构设计与仿真[J]. 工程设计学报, 2011, 18(1): 34-38. SHEN Ling, MENG Qingyun, YU Hongliu. Design and simulation of leg prosthesis structure based on virtual prototype technology[J]. Journal of Engineering Design, 2011, 18(1): 34-38.
[35] MOURAGNON E, LHUILLIER M, DHOME M, et al. Monocular vision based SLAM for mobile robots[C]//IEEE International Conference on Pattern Recognition. Hong Kong, China, 2006, 3: 1027-1031.
[36] PRATT J, CHEW C M, TORRES A, et al. Virtual model control: An intuitive approach for bipedal locomotion[J]. The International Journal of Robotics Research, 2001, 20(2): 129-143.
[37] YUAN Shaoqiang, LIU Zhong, LI Xingshan. Modeling and simulation of robot based on Matlab/SimMechanics[C]//Proceedings of the 27th Chinese Control Conference. Kunming, China, 2008: 161-165.
[38] XU Guozheng, SONG Aiguo, LI Huijun. Control system design for an upper-limb rehabilitation robot[J]. Advanced Robotics, 2011, 25(1-2): 229-251.
[39] RARNJANI A N, CORSS P A. A Kalman filter model of an integrated land vehicle navigation system[J]. Journal of Navigation, 1995, 48(2): 293-302.
[40] HARDYK A T T. Force and power-velocity relationships in a multi-joint movement[D]. Pennsylvania State: The Pennsylvania State University, 2000: 102-123.
[41] FENN W O, MARSH B S. Muscular force at different speeds of shortening[J]. The Journal of Physiology, 1935, 85(3): 277-297.
[42] POLISSAR M J. Physical chemistry of contractile process in muscle. I. A physicochemical model of contractile mechanism[J]. The American Journal of Physiology, 1952, 168(3): 766-811.
[43] SHADMEHR R, ARBIB M. A mathematical analysis of the force-stiffness characteristics of muscles in control of a single joint system[J]. Biological Cybernetics, 1992, 66(6): 463-477.
[44] VISSER J J, HOOGKAMER J E, BOBBERT M F, et al. Length and moment arm of human leg muscles as a function of knee and hip-joint angles[J]. European Journal of Applied Physiology and Occupational Physiology, 1990, 61(5-6): 453-460.
[45] AN K N, TAKAHASHI K, HARRIGAN T P, et al. Determination of muscle orientations and moment arms[J]. Journal of Biomechanical Engineering, 1984, 106(3): 280-282.
[46] OSU R, FRANKLIN D W, KATO H, et al. Short-and long-term changes in joint co-contraction associated with motor learning as revealed from surface EMG[J]. Journal of Neurophysiology, 2002, 88(2): 991-1004.
[47] 孙棕檀. 刚柔耦合系统分析动力学建模研究[D]. 哈尔滨: 哈尔滨工程大学, 2013: 44-56. SUN Zongtan. Research on dynamic modeling analysis of rigid flexible coupling system[D]. Harbin: Harbin Engineering University, 2013: 44-56.
[48] MENG Wei, DING Bo, ZHOU Zude, et al. An EMG-based force prediction and control approach for robot-assisted lower limb rehabilitation[J]. IEEE International Conference on Systems, Man, and Cybernetics. San Diego, USA, 2014: 2198-2203.
[49] 陈贵亮, 李长鹏, 赵月, 等. 下肢外骨骼康复机器人的动力学建模及神经网络辨识仿真[J]. 机械设计与制造, 2013, (11): 197-200. CHEN Guiliang, LI Changpeng, ZHAO Yue, et al. Dynamic modeling and neural network identification simulation for lower limbs exoskeletons rehabilitation robot[J]. Mechanical Design and Manufacture, 2013, (11): 197-200.
[50] KARAVAS N, AJOUDANI A, TSAGARAKIS N, et al. Tele-impedance based assistive control for a compliant knee exoskeleton[J]. Robotics and Autonomous Systems, 2014, doi: 10.1016/j.robot.2014.09.027.
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