踝助力外衣的研制与跖屈肌群肌电信号评价

doi:10.3901/JME.2023.17.067

机械工程学报 ›› 2023, Vol. 59 ›› Issue (17): 67-78.doi: 10.3901/JME.2023.17.067

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踝助力外衣的研制与跖屈肌群肌电信号评价

张雷雨¹, 叶土仙¹, 高翔¹, 张斐然², 李剑锋¹, 苏鹏³

1. 北京工业大学先进制造技术北京市重点实验室北京 100124;
2. 武汉第二船舶设计研究所武汉 430064;
3. 北京信息科技大学机电工程学院北京 100192

收稿日期:2022-09-12 修回日期:2022-11-26 出版日期:2023-09-05 发布日期:2023-11-16
通讯作者: 李剑锋(通信作者),男,1964年出生,教授,博士研究生导师。主要研究方向为机器人机构学和穿戴外骨骼技术。E-mail:lijianfeng@bjut.edu.cn
作者简介:张雷雨,男,1988年出生,博士,副教授。主要研究方向为上肢康复机器人及下肢柔性助力设备。E-mail:zhangleiyu@bjut.edu.cn
基金资助:
北京市自然科学基金（3202003，19L2018）、国家重点研发计（2018YFB1307004）和国家自然科学基金（52005045）资助项目。

Design and EMG Signal Evaluation of Ankle Assistance Exosuit

ZHANG Leiyu¹, YE Tuxian¹, GAO Xiang¹, ZHANG Feiran², LI Jianfeng¹, SU Peng³

1. Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100124;
2. Wuhan Second Ship Design and Research Institute, Wuhan 430064;
3. School of Electromechanical Engineering, Beijing Information Science and Technology University, Beijing 100192

Received:2022-09-12 Revised:2022-11-26 Online:2023-09-05 Published:2023-11-16

摘要/Abstract

摘要： 随着国防装备发展及人口老龄化加剧，战场士兵、部队后勤及老年人口等对下肢柔性外骨骼的需求急剧升高，进而研制了穿戴性好、人机相容性高、助力性能优的便携式踝助力外衣系统。基于踝关节生理特征与人体下肢参数，对踝助力外衣本体和驱动单元进行工效学设计和实物研制，并将驱动单元放置于腰部，尽可能降低小腿和足部的附加质量。基于踝关节生物力矩特征，建立期望辅助力模型，采用实验测量的办法，获得助力外衣及局部软组织的系统刚度，将期望辅助力模型转换为驱动单元的位移模型。基于人体下肢步态的周期性，设计以迭代学习控制算法为核心的控制器，通过迭代学习历史时刻的输出误差，对期望辅助力模型进行不断追踪。为评估助力外衣的助力效果，通过测量穿戴者的跖屈肌肉群肌电信号，分析肌肉激活程度和疲劳变化：在踝助力外衣的辅助下，不同行走速度的肌肉激活程度均明显下降，以腓肠肌外侧变化最为显著，腓肠肌内侧肌肉激活程度平均下降了9.62%±1.12%；平均功率频率和中位频率的变化斜率绝对值均得到一定程度的下降，肌肉疲劳速率下降、疲劳程度降低，进而下肢行走耐力增强。

关键词: 柔性外骨骼, 踝关节助力, 迭代学习控制, 肌电信号, 性能评估

Abstract: With the development of national defense equipment and the aggravation of population aging, the demand of lower limb flexible exoskeletons for battlefield soldiers, army logistics and the elderly population has risen sharply. Based on this urgent demand, a portable ankle assistance Exosuit system with good wearability, high human-machine compatibility and excellent assistance performance has been developed. According to the physiological characteristics of the ankle joint and the parameters of lower limbs, the ergonomic design and development of the Exosuit body and driving unit are achieved where the driving unit is placed at the waist to reduce the added mass of legs and feet as much as possible. Based on the biological torque of the ankle joint, the model of expected auxiliary force is established. The system stiffness of the assistance Exosuit and local soft tissue is obtained by the experimental measurement. Then the established model is transformed into the displacement model of the driving unit. Based on the gait periodicity of lower limbs, a controller with iterative learning control algorithm as the core is designed to track the force model through iteratively learning the output errors of historical time. In order to evaluate the assistance performance of the Exosuit system, the degree of muscle activation and fatigue changes were analyzed by measuring the EMG signals of the plantarflexion muscles. Under the condition of Power-ON, the degree of muscle activation under three walking speeds decreased significantly, especially lateral gastrocnemius muscle. The muscle activation degree of the medial gastrocnemius muscle decreased by an average of 9.62% ± 1.12%. The absolute value of the change slope of mean power frequency (MPF) and median frequency (MF) descended obviously. Hence, the rate and degree of muscle fatigue decreased and the walking endurance of lower limbs increased.

Key words: soft exoskeleton, ankle assistance, iterative learning control, EMG signal, performance evaluation

中图分类号:

TP24

张雷雨, 叶土仙, 高翔, 张斐然, 李剑锋, 苏鹏. 踝助力外衣的研制与跖屈肌群肌电信号评价[J]. 机械工程学报, 2023, 59(17): 67-78.

ZHANG Leiyu, YE Tuxian, GAO Xiang, ZHANG Feiran, LI Jianfeng, SU Peng. Design and EMG Signal Evaluation of Ankle Assistance Exosuit[J]. Journal of Mechanical Engineering, 2023, 59(17): 67-78.

参考文献

[1] 赵新刚,谈晓伟,张弼. 柔性下肢外骨骼机器人研究进展及关键技术分析[J]. 机器人,2020,42(3):111-130. ZHAO Xingang,TAN Xiaowei,ZHANG Bi. Development of soft lower extremity exoskeleton and its key technologies:A survey[J]. Robot,2020,42(3):365-384.
[2] KIM J,LEE G,HEIMGRATNER R,et al. Reducing the metabolic rate of walking and running with a versatile,portable Exosuit[J]. Science,2019,365(6454):668-672.
[3] PARK J,PARK H,KIM J. Performance estimation of the lower limb exoskeleton for plantarflexion using surface Electromyography (sEMG) signals[J]. Journal of Biomechanical Science and Engineering,2017,12(2):1-9.
[4] 李剑锋,李国通,张雷雨,等. 穿戴式柔性下肢助力机器人发展现状及关键技术分析[J]. 自动化学报,2020,46(3):427-438. LI Jianfeng,LI Guotong,ZHANG Leiyu,et al. Advances and key techniques of soft wearable lower limb power-assisted robots[J]. Acta Automatica Sinica,2020,46(3):427-438.
[5] SCHMIDT K,DUARTE J E,GRIMMER M. The Myosuit:Bi-articular anti-gravity Exosuit that reduces hip extensor activity in sitting transfers[J]. Frontiers in Neurorobotics,2017,11(57):1-16.
[6] TIAN M,WANG X,WANG J,et al. Design of a lower limb exoskeleton driven by tendon-sheath artificial muscle[C]//2019 IEEE International conference on robotics and biomimetics (ROBIO),Piscataway:IEEE,2019:91-96.
[7] TU X,HUANG J,HE J. Leg hybrid rehabilitation based on hip-knee exoskeleton and ankle motion induced by FES[C]//2016 International conference on Advanced Robotics and Mechatronics (ICARM),Piscataway:IEEE,2016:237-242.
[8] DING Y,GALIANA I,ASBECK A T,et al. Biomechanical and physiological evaluation of multi-joint assistance with soft Exosuits[J]. IEEE Transactions on Neural Systems & Rehabilitation Engineering,2017,25(2):119-130.
[9] AWAD L N,BAE J,O'DONNELL K,et al. A soft robotic Exosuit improves walking in patients after stroke[J]. Science Translational Medicine,2017,9(400):eaai9084.
[10] DING Y,KIM M,KUINDERSMA S,et al. Human-in-the-loop optimization of hip assistance with a soft Exosuit during walking[J]. Science Robotics,2018,3(15):eaai5438.
[11] HASHIMOTO Y,NAKANISHI Y,SAGA N,et al. Development of gait assistive device using pneumatic artificial muscle[C]//2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS),Piscataway:IEEE,2016:710-713.
[12] 刘王智懿,郑银环,孙健铨,等. 轻量型柔性下肢助力外骨骼的设计及性能实验[J]. 机器人,2021(4):433-442. LIUWANG Zhiyi,ZHEN Yinhuan,SUN Jianquan,et al. Design and performance experiment of a lightweight flexible lower-limb exoskeleton[J]. Robot,2021(4):433-442.
[13] JIN S,IWAMOTO N,HASHIMOTO K,et al. Experimental evaluation of energy efficiency for a soft wearable robotic suit[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering,2017,25(8):1192-1201.
[14] JOHN S W,MURAKAMI K,KOMATSU M,et al. Cross-wire assist suit concept for mobile and lightweight multiple degree of freedom hip assistance[C]//2017 International Conference on Rehabilitation Robotics (ICORR),Piscataway:IEEE,2017:387-393.
[15] SCHACHE A G,BLANCH P D,DORN T W,et al. Effect of running speed on lower limb joint kinetics[J]. Medicine & Science in Sports & Exercise,2011,43(7):1260-1271.
[16] DEMBIA C L,SILDER A,UCHIDA T K,et al. Simulating ideal assistive devices to reduce the metabolic cost of walking with heavy loads[J]. PLOS ONE,2017,12(7):e0180320.
[17] QUINLIVAN B T,LEE S,MALCOLM P,et al. Assistance magnitude versus metabolic cost reductions for a tethered multiarticular soft exosuit[J]. Science Robotics,2017,2(2):eaah4416.
[18] TAKAHASHI K Z,LEWEK M D,SAWICKI G S. A neuromechanics-based powered ankle exoskeleton to assist walking post-stroke:a feasibility study[J]. Journal of NeuroEngineering and Rehabilitation,2015,12(1):1-13.
[19] 王文东,肖孟涵,孔德智,等. 基于人机耦合模型的上肢康复外骨骼闭环PD迭代控制方法[J]. 机械工程学报,2021,57(21):11-21. WANG Wendong,XIAO Menghan,KONG Dezhi,et al. Closed-loop PD iterative control method for upper limb rehabilitation exoskeleton based on human-robot coupling model[J]. Journal of Mechanical Engineering,2021,57(21):11-21.
[20] CHEN Q,GUO S,SUN L,et al. IMU-based optimization control of a soft Exosuit for hip extension and flexion assistance[J]. Journal of Mechanisms and Robotics,2021,13(2):1-29.
[21] 万诗龙. 可穿戴下肢柔性外骨骼助力系统设计[D]. 南京:东南大学,2017. WAN Shilong. Design of the power system of wearable and flexible lower-limb exoskeleton[D]. Nanjing:Southeast University,2017.
[22] GATE D H. Catheterizing ankle function during stair ascent,descent,and level walking for ankle prosthesis and orthosis design[D]. Boston:Boston University,2004.
[23] 王子帅,傅宏俊,钟智丽. 柔性外骨骼服装面料的性能[J].上海纺织科技,2020,48(11):9-12. WANG Zhishuai,FU Hongjun,ZHONG Zhili. Performance of soft exoskeleton clothing fabric[J]. Shanghai Textile Science & Technology,2020,48(11):9-12.
[24] ASBECK A T,ROSSI S M M D,HOLT K G,et al. A biologically inspired soft Exosuit for walking assistance[J]. The International Journal of Robotics Research,2015,34(6):744-762.
[25] XILOYANNIS M,CHIARADIA D,FRISOLI A,et al.Physiological and kinematic effects of a soft Exosuit on arm movements[J]. Journal of NeuroEngineering and Rehabilitation,2019,16(29):11-26.
[26] 杨景慧,耿喜臣,卫晓阳,等. 下肢蹬力专项训练对模拟空战连续载荷下蹬力耐量及肌肉疲劳的影响[J]. 航天医学与医学工程,2021,34(6):415-420. YANG Jinghui,GEN Xicheng,WEI Xiaoyang,et al. Effects of special training for lower limb pedaling force on pedaling force tolerance and muscle fatigue under continuous load in simulated air combat[J]. Space Medicine & Medical Engineering,2021,34(6):415-420.
[27] 董雪芬. 不同强度快速伸膝运动对股四头肌肌电图平均功率频率和输出功率的影响[J]. 浙江师范大学学报,2014,37(4):475-480. DONG Xuefen. The effect of different intensity of fast knee extension exercise on the stock four muscle's MPF and the output power[J]. Journal of Zhejiang Normal University,2014,37(4):475-480.
[28] KANKAANP M,TAIMELA S,WEBBER C L,et al. Lumbar paraspinal muscle fatigability in repetitive isoinertial loading:EMG spectral indices,borg scale and endurance time[J]. European Journal of Applied Physiology and Occupational Physiology,1997,76(3):236-242.

踝助力外衣的研制与跖屈肌群肌电信号评价

Design and EMG Signal Evaluation of Ankle Assistance Exosuit

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