Neuro-fuzzy control of a robotic exoskeleton with EMG signals

Kazuo Kiguchi, Takakazu Tanaka, Toshio Fukuda

Research output: Contribution to journalArticlepeer-review

325 Citations (Scopus)


We have been developing robotic exoskeletons to assist motion of physically weak persons such as elderly, disabled, and injured persons. The robotic exoskeleton is controlled basically based on the electromyogram (EMG) signals, since the EMG signals of human muscles are important signals to understand how the user intends to move. Even though the EMG signals contain very important information, however, it is not very easy to predict the user's upper-limb motion (elbow and shoulder motion) based on the EMG signals in real-time because of the difficulty in using the EMG signals as the controller input signals. In this paper, we propose a robotic exoskeleton for human upper-limb motion assist, a hierarchical neuro-fuzzy controller for the robotic exoskeleton, and its adaptation method.

Original languageEnglish
Pages (from-to)481-490
Number of pages10
JournalIEEE Transactions on Fuzzy Systems
Issue number4
Publication statusPublished - Aug 2004
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics


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