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Chin J Eng Design  2023, Vol. 30 Issue (3): 362-371    DOI: 10.3785/j.issn.1006-754X.2023.00.037
Robotic and Mechanism Design     
Design and mechanism optimization of lower limb exoskeleton based on human dynamics analysis
Guiliang CHEN(),Zihao LI,Chao CAI,Yongchao LI,Dong YANG()
School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China
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Abstract  

In order to design a passive lower limb exoskeleton with good assisting effect, an optimal design method of lower limb exoskeleton was proposed based on the analysis of the motion and mechanical characteristics of human walking and the mechanical performance of the relevant major muscle groups. Through the human walking experiment, the kinematics information and plantar reaction force were obtained to drive the simulation of Anybody, and the mechanical data of lower limb muscles during walking were obtained. With the help of Hill muscle model, a simplified model of muscle?tendon?bone of hip joint in the sagittal plane of the human body was established, and a virtual torsion spring was added to simulate the role of exoskeleton, forming an integrated model of human body and exoskeleton. On this basis, the human-computer interaction force and the muscle activation of the wearer were quantitatively analyzed when wearing the assisted exoskeleton. The calculation models of muscle activation degree and metabolizable energy with torsion spring stiffness as variable were established, and the stiffness of virtual torsion spring was optimized by particle swarm optimization to obtain the optimal value with the goal of minimum metabolizable energy. Based on this, the design scheme of hip joint assisted exoskeleton mechanism was proposed, and the difference between the auxiliary torque of the mechanism and the virtual torsion spring torque was minimized as the goal to optimize, and the optimal values of the tension spring stiffness and the size of each connecting rod were obtained as the design parameters of the exoskeleton mechanism. At the same time, the prototype of hip joint assisted exoskeleton was made and the experiment of assisted walking was carried out. The results showed that the metabolic energy of human body was significantly reduced when wearing the assisted exoskeleton. The research method can provide reference for the design and analysis of other lower limb exoskeletons.



Key wordsassisted exoskeleton      human dynamics      human modeling      motion assistance      Hill muscle model     
Received: 30 September 2022      Published: 06 July 2023
CLC:  TP 242  
Corresponding Authors: Dong YANG     E-mail: guiliang_chen@sina.com;88292946@qq.com
Cite this article:

Guiliang CHEN,Zihao LI,Chao CAI,Yongchao LI,Dong YANG. Design and mechanism optimization of lower limb exoskeleton based on human dynamics analysis. Chin J Eng Design, 2023, 30(3): 362-371.

URL:

https://www.zjujournals.com/gcsjxb/10.3785/j.issn.1006-754X.2023.00.037     OR     https://www.zjujournals.com/gcsjxb/Y2023/V30/I3/362


基于人体动力学分析的下肢外骨骼助力设计及机构优化

为设计助力效果良好的被动式下肢外骨骼,基于对人体行走的运动和力学特征以及相关主要肌群的力学表现的分析,提出了一种下肢外骨骼优化设计方法。通过开展人体行走实验,获取人体运动学信息和足底反力,并将其用于驱动Anybody仿真,从而得到人体行走过程中下肢肌肉的力学数据。借助Hill肌肉模型建立人体矢状面内的髋关节肌肉-肌腱-骨骼简化模型,并在该模型中添加虚拟扭簧以模拟助力外骨骼的作用,形成人体-外骨骼一体化模型。在此基础上,对穿戴助力外骨骼行走时的人机交互力以及穿戴者的肌肉激活情况进行量化分析。建立以扭簧刚度为变量的肌肉激活程度、代谢能计算模型,并以代谢能最低为目标,利用粒子群算法对虚拟扭簧的刚度进行优化以获得最优值。据此,提出髋关节助力外骨骼机构设计方案,并以机构的辅助力矩与虚拟扭簧力矩差值最小为目标进行优化,得到机构中拉簧刚度和各个连杆尺寸的最优值,作为外骨骼机构设计参数。同时,制作髋关节助力外骨骼样机并开展助力行走实验。结果表明,穿戴该助力外骨骼行走时人体代谢能降低效果显著。研究方法可为其他下肢外骨骼的设计和分析提供借鉴。


关键词: 助力外骨骼,  人体动力学,  人体建模,  运动助力,  Hill肌肉模型 
Fig.1 Division of a single gait cycle
Fig.2 Dynamics simulation curves of hip joint during a single gait cycle
Fig.3 Hill muscle model
肌肉Fmax/NLm0/cmLt0/cmPCSA/cm2

vmax/

(m/s)

股匠肌1 385.452 08.973 733.292 015.393 90.897 3
臀大肌716.419 317.329 46.945 37.960 21.732 9
腘绳肌2 607.622 59.775 335.174 228.973 59.775 2
髂腰肌565.556 35.278 09.742 96.283 95.278 0
Table 1 Basic parameters of hip joint muscles
Fig.4 Simplified model of hip joint muscle‒tendon‒bone
Fig.5 Comparison of muscle strength and equivalent muscle strength of various hip joint muscle groups
Fig.6 Comparison of hip joint torque
Fig.7 Hip joint-exoskeleton coupling model and exoskeleton mechanism principle
Fig.8 General framework for inverse solution of muscle dynamics
Fig.9 Schematic diagram of hip joint exoskeleton assistance
Fig.10 Influence of assisted exoskeleton on hip joint torque
Fig.11 Comparison of metabolic power curves of hip joint muscle groups with and without assistance
Fig.12 Comparison of auxiliary torque of hip joint assisted exoskeleton
Fig.13 Hip joint assisted exoskeleton experimental platform
Fig.14 EMG signal acquisition results of hip joint extensor and flexor muscle groups
Fig.15 Average EMG signal of hip joint extensor and flexor muscle groups
[1]   TUDOR-LOCKE C, JOHNSON W D, KATZMARZYK P T. Accelerometer-determined steps per day in US adults[J]. Medicine & Science in Sports & Exercise, 2009, 41(7): 1384-1391.
[2]   ZIEGLER J, REITER A, GATTRINGER H, et al. Simultaneous identification of human body model parameters and gait trajectory from 3D motion capture data[J]. Medical Engineering & Physics, 2020, 84(3): 193-202.
[3]   GROOTE F D, FALISSE A. Perspective on musculoskeletal modelling and predictive simulations of human movement to assess the neuromechanics of gait[J]. Proceedings of the Royal Society B: Biological Sciences, 2021, 288(1946): 2432-2442.
[4]   AN K, LIU Y, LI Y, et al. Energetic walking gaits studied by a simple actuated inverted pendulum model[J]. Journal of Mechanical Science & Technology, 2018, 32(5): 2273-2281.
[5]   YE D, GALIANA I, ASBECK A T, et al. Biomechanical and physiological evaluation of multi-joint assistance with soft exosuits[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2017, 25(2): 119-130.
[6]   UMBERGER B R, RUBENSON J. Understanding muscle energetics in locomotion: new modeling and experimental approaches[J]. Exercise & Sport Sciences Reviews, 2011, 39(2): 59-67.
[7]   BARAZESH H, SHARBAFI M A. A biarticular passive exosuit to support balance control can reduce metabolic cost of walking[J]. Bioinspiration & Biomimetics, 2020, 15(3): 1024-1042.
[8]   HAUFE F L, WOLF P, RIENER R, et al. Biomechanical effects of passive hip springs during walking[J]. Journal of Biomechanics, 2020, 98: 109432.
[9]   SHEN Z, SAM S, ALLISON G, et al. A simulation-based study on a clutch-spring mechanism reducing human walking metabolic cost[J]. International Journal of Mechanical Engineering and Robotics Research, 2018, 7(1): 55-60.
[10]   胡冰山,程科,陆盛,等.变刚度储能助力髋外骨骼设计及助力效果仿真[J].系统仿真学报,2022,34(5):1090-1100. doi:10.16182/j.issn1004731x.joss.20-0994
HU B S, CHENG K, LU S, et al. Design of variable stiffness energy storage walking assist hip exoskeleton and simulation of assistance effect[J]. Journal of System Simulation, 2022, 34(5): 1090-1100.
doi: 10.16182/j.issn1004731x.joss.20-0994
[11]   DORN T W, SCHACHE A G, PANDY M G. Muscular strategy shift in human running: dependence of running speed on hip and ankle muscle performance[J]. Journal of Experimental Biology, 2012, 215(11): 1944-1959.
[12]   LI Z, LIU H, YIN Z, et al. Muscle synergy alteration of human during walking with lower limb exoskeleton[J]. Frontiers in Neuroscience, 2018, 29(12): 1050-1059.
[13]   ARNOLD E M, DELP S L. Fibre operating lengths of human lower limb muscles during walking[J]. Philosophical Transactions of the Royal Society B: Biological Sciences, 2011, 366(1570): 1530-1539.
[14]   SAWICKI G S, KHAN N S. A simple model to estimate plantarflexor muscle-tendon mechanics and energetics during walking with elastic ankle exoskeletons[J]. IEEE Transactions on Biomedical Engineering, 2016, 63(5): 914-923.
[15]   LEE H J, LEE S, CHANG W H, et al. A wearable hip assist robot can improve gait function and cardiopulmonary metabolic efficiency in elderly adults[J]. IEEE Transactions on Neural Systems & Rehabilitation Engineering, 2017, 252(9): 1549-1557.
[16]   NASIRI R, RAYATI M, AHMADABADI M N. Feedback from mono-articular muscles is sufficient for exoskeleton torque adaptation[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2019, 27(10): 2097-2106.
[17]   ZAJAC F E. Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control[J]. Critical Reviews in Biomedical Engineering, 1989, 17(4): 359-411.
[18]   BOGEY R A, BARNSE L A. An EMG-to-force processing approach for estimating in vivo hip muscle forces in normal human walking[J]. IEEE Transactions on Neural Systems & Rehabilitation Engineering, 2016, 25(8): 1172-1179.
[19]   WENINHANDL J T, BENNETT H J. Musculoskeletal model choice influences hip joint load estimations during gait[J]. Journal of Biomechanics, 2019, 91: 124-132.
[20]   CHEN W B, WU S, ZHOU T C, et al. On the biological mechanics and energetics of the hip joint muscle-tendon system assisted by passive hip exoskeleton[J]. Bioinspiration & Biomimetics, 2019, 14(1): 016012.
[21]   王存金,董林杰,李杰,等.基于人行走能耗分析的踝关节外骨骼设计[J].机械工程学报,2021,57(19):79-92. doi:10.3901/jme.2021.19.008
WANG C J, DONG L J, LI J, et al. Design of ankle exoskeleton based on analysis on energy cost of human walking[J]. Journal of Mechanical Engineering, 2021, 57(19): 79-92.
doi: 10.3901/jme.2021.19.008
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