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面向人机融合的智能动力下肢假肢研究现状与挑战

王启宁 郑恩昊 陈保君 麦金耿

王启宁, 郑恩昊, 陈保君, 麦金耿. 面向人机融合的智能动力下肢假肢研究现状与挑战. 自动化学报, 2016, 42(12): 1780-1793. doi: 10.16383/j.aas.2016.y000007
引用本文: 王启宁, 郑恩昊, 陈保君, 麦金耿. 面向人机融合的智能动力下肢假肢研究现状与挑战. 自动化学报, 2016, 42(12): 1780-1793. doi: 10.16383/j.aas.2016.y000007
WANG Qi-Ning, ZHENG En-Hao, CHEN Bao-Jun, MAI Jin-Geng. Recent Progress and Challenges of Robotic Lower-limb Prostheses for Human-robot Integration. ACTA AUTOMATICA SINICA, 2016, 42(12): 1780-1793. doi: 10.16383/j.aas.2016.y000007
Citation: WANG Qi-Ning, ZHENG En-Hao, CHEN Bao-Jun, MAI Jin-Geng. Recent Progress and Challenges of Robotic Lower-limb Prostheses for Human-robot Integration. ACTA AUTOMATICA SINICA, 2016, 42(12): 1780-1793. doi: 10.16383/j.aas.2016.y000007

面向人机融合的智能动力下肢假肢研究现状与挑战

doi: 10.16383/j.aas.2016.y000007
基金项目: 

国家自然科学基金 61020106005

北京市科技计划项目 Z151100003715001

国家自然科学基金 61005082

国家自然科学基金 61533001

北京市科技计划项目 Z151100000915073

详细信息
    作者简介:

    郑恩昊 中国科学院自动化研究所助理研究员.2016年获北京大学工学院博士学位.主要研究方向为神经接口, 类脑机器人.E-mail:enhao.zheng@ia.ac.cn

    陈保君  意大利圣安娜高等研究院博士后.2016年获北京大学工学院博士学位.主要研究方向为神经接口, 康复工程.E-mail:chenbaojun@pku.edu.cn

    麦金耿  北京大学工学院博士后. 2016年获北京航空航天大学博士学位.主要研究方向为机器人和智能制造. E-mail:jingengmai@pku.edu.cn

    通讯作者:

    王启宁  北京大学工学院研究员.2009年获北京大学力学系博士学位.主要研究方向为智能机器人, 康复工程.本文通信作者.E-mail:qiningwang@pku.edu.cn

Recent Progress and Challenges of Robotic Lower-limb Prostheses for Human-robot Integration

Funds: 

National Natural Science Foundation of China 61020106005

Beijing Municipal Science and Technology Project Z151100003715001

National Natural Science Foundation of China 61005082

National Natural Science Foundation of China 61533001

Beijing Municipal Science and Technology Project Z151100000915073

More Information
    Author Bio:

    Assistant professor at The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences. He received his Ph. D. degree from Peking University in 2016. His research interest covers neural interfaces and brain-inspired robotics

    Postdoctor at the BioRobotics Institute, Scuola Superiore Sant0Anna, Italy. He received his Ph. D. degree from Peking University in 2016. His research interest covers neural interfaces and rehabilitation engineering

    Postdoctor at the College of Engineering, Peking University. He received his Ph. D. degree from Beihang University in 2016. His research interest covers robotics and intelligent manufactoring

    Corresponding author: WANG Qi-Ning Professor at the College of Engineering, Peking University. He received his Ph. D. degree from Peking University in 2009. His research interest covers robotics and rehabilitation engineering. Corresponding author of this paper
  • 摘要: 智能动力下肢假肢在残疾人生活中起着越来越重要的作用.解决人-智能假肢-环境融合中的关键科学问题是实现假肢穿戴者安全、流畅运动的必要条件.本文针对此问题,综述了面向人机融合的智能动力下肢假肢研究,包括智能动力下肢假肢的仿生结构和控制方法、人体运动意图识别、复杂环境下的人-智能假肢融合、以及用于下肢假肢的感知替代和反馈,深入探讨了智能动力下肢假肢人机融合研究中所面临的挑战和问题,最后,本文对该领域的未来发展方向进行了展望和总结.
    1)  本文责任编委  王卫群
  • 图  1  智能动力下肢假肢((a) MIT智能动力小腿假肢[2]; (b)智能动力小腿假肢Odyssey[21]; (c)储能小腿假肢AMP-foot 2.0[5]; (d)含膝、踝关节的智能动力大腿假肢[24]; (e)含踝、趾关节的智能动力假肢PANTOE[6]; (f)智能动力小腿假肢PKU-RoboTPro[7])

    Fig.  1  Robotic lower-limb prostheses ((a) MIT powered ankle-foot prosthesis[2]; (b) Odyssey[21]; (c) AMP-foot 2.0[5]; (d) Vanderbilt powered lower-limb prosthesis[24]; (e) PANTOE[6]; (f) PKU-RoboTPro[7])

    图  2  智能动力下肢假肢的分层控制策略

    Fig.  2  Hierarchical control strategy of robotic lower-limb prostheses

    图  3  基于sEMG运动意图识别研究((a)残疾人穿戴智能动力小腿假肢, 通过sEMG主动控制在不同角度的斜坡上行走[34]; (b)大腿肌肉重定向手术示意图(上), 重定向手术后通过收缩大腿肌肉来反映踝关节的跖屈和背屈[37])

    Fig.  3  Human intent recognition based on sEMG signals ((a) sEMG-based volitional control of robotic transtibial prosthesis, and the amputee walks on ramps with different angles[34]; (b) Target muscle reinnervation (TMR)(upper half), sEMG signals of ankle dorsiflexion and ankle plantarflexion through TMR muscles (bottom half)[37])

    图  4  基于非接触式电容传感的运动意图识别((a)非接触式电容传感在小腿假肢上测量原理示意图; (b)基于非接触式电容传感的运动意图识别研究,与小腿智能动力假肢穿戴示意图)

    Fig.  4  Lower-limb motion intent recognition based on noncontact capacitive sensing ((a) The sensing principle of noncontact capacitive sensing on transtibial prosthesis; (b) A study on noncontact capacitive sensing based locomotion transition recognition with robotic prosthesis, and its placement on human body)

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  • 收稿日期:  2016-02-01
  • 录用日期:  2016-11-17
  • 刊出日期:  2016-12-01

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