Learning to walk with a robotic ankle exoskeleton

被引:222
|
作者
Gordon, Keith E.
Ferris, Daniel P.
机构
[1] Univ Michigan, Div Kinesiol, Ann Arbor, MI 48109 USA
[2] Univ Michigan, Dept Biomed Engn, Ann Arbor, MI 48109 USA
[3] Univ Michigan, Dept Phys Med & Rehabil, Ann Arbor, MI 48109 USA
关键词
gait; motor learning; biomechanics; powered orthosis; locomotion; EMG;
D O I
10.1016/j.jbiomech.2006.12.006
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
We used a lower limb robotic exoskeleton controlled by the wearer's muscle activity to study human locomotor adaptation to disrupted muscular coordination. Ten healthy subjects walked while wearing a pneumatically powered ankle exoskeleton on one limb that effectively increased plantar flexor strength of the soleus muscle. Soleus electromyography amplitude controlled plantar flexion assistance from the exoskeleton in real time. We hypothesized that subjects' gait kinematics would be initially distorted by the added exoskeleton power, but that subjects would reduce soleus muscle recruitment with practice to return to gait kinematics more similar to normal. We also examined the ability of subjects to recall their adapted motor pattern for exoskeleton walking by testing subjects on two separate sessions, 3 days apart. The mechanical power added by the exoskeleton greatly perturbed ankle joint movements at first, causing subjects to walk with significantly increased plantar flexion during stance. With practice, subjects reduced soleus recruitment by similar to 35% and learned to use the exoskeleton to perform almost exclusively positive work about the ankle. Subjects demonstrated the ability to retain the adapted locomotor pattern between testing sessions as evidenced by similar muscle activity, kinematic and kinetic patterns between the end of the first test day and the beginning of the second. These results demonstrate that robotic exoskeletons controlled by muscle activity could be useful tools for testing neural mechanisms of human locomotor adaptation. (c) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2636 / 2644
页数:9
相关论文
共 50 条
  • [1] Learning to walk with an adaptive gain proportional myoelectric controller for a robotic ankle exoskeleton
    Koller, Jeffrey R.
    Jacobs, Daniel A.
    Ferris, Daniel P.
    Remy, C. David
    JOURNAL OF NEUROENGINEERING AND REHABILITATION, 2015, 12
  • [2] Learning to walk with an adaptive gain proportional myoelectric controller for a robotic ankle exoskeleton
    Jeffrey R. Koller
    Daniel A. Jacobs
    Daniel P. Ferris
    C. David Remy
    Journal of NeuroEngineering and Rehabilitation, 12
  • [3] Medial Gastrocnemius Myoelectric Control of a Robotic Ankle Exoskeleton
    Kinnaird, Catheine R.
    Ferris, Daniel P.
    IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2009, 17 (01) : 31 - 37
  • [4] Invariant ankle moment patterns when walking with and without a robotic ankle exoskeleton
    Kao, Pei-Chun
    Lewis, Cara L.
    Ferris, Daniel P.
    JOURNAL OF BIOMECHANICS, 2010, 43 (02) : 203 - 209
  • [5] Haptic Adaptive Feedback to Promote Motor Learning With a Robotic Ankle Exoskeleton Integrated With a Video Game
    Asin-Prieto, Guillermo
    Martinez-Exposito, Aitor
    Barroso, Filipe O.
    Urendes, Eloy J.
    Gonzalez-Vargas, Jose
    Alnajjar, Fady S.
    Gonzalez-Alted, Carlos
    Shimoda, Shingo
    Pons, Jose L.
    Moreno, Juan C.
    FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY, 2020, 8
  • [6] Virtual Neuromuscular Control for Robotic Ankle Exoskeleton Standing Balance
    Yin, Kaiyang
    Jin, Yantao
    Du, Haojie
    Xue, Yaxu
    Li, Pengfei
    Ma, Zhengsen
    MACHINES, 2022, 10 (07)
  • [7] Real-Time Walk Detection for Robotic Hip Exoskeleton Applications
    Cho, Hang Man
    Kang, Inseung
    Park, Dongho
    Molinaro, Dean D.
    Young, Aaron J.
    2022 INTERNATIONAL SYMPOSIUM ON MEDICAL ROBOTICS (ISMR), 2022,
  • [8] Development and Validation of Robotic Ankle Exoskeleton With Parallel Nonlinear Elastic Actuator
    Chen B.
    Shi C.
    Zi B.
    Qin L.
    Xu Q.
    Journal of Mechanical Design, 2024, 146 (11)
  • [9] Predicting Neuromuscular Engagement to Improve Gait Training With a Robotic Ankle Exoskeleton
    Harshe, Karl
    Williams, Jack R.
    Hocking, Toby D.
    Lerner, Zachary F.
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2023, 8 (08) : 5055 - 5060
  • [10] Preliminary Validation of Proportional Myoelectric Control of A Commercially Available Robotic Ankle Exoskeleton
    Hybart, Rachel L.
    Ferris, Daniel P.
    2022 INTERNATIONAL CONFERENCE ON REHABILITATION ROBOTICS (ICORR), 2022,