TY - JOUR
T1 - Neuro-fuzzy control of a robotic exoskeleton with EMG signals
AU - Kiguchi, Kazuo
AU - Tanaka, Takakazu
AU - Fukuda, Toshio
N1 - Funding Information:
Manuscript received October 9, 2003; revised June 3, 2004. This work was supported in part by the Mazda Foundation. K. Kiguchi and T. Tanaka are with the Department of Advanced Systems Control Engineering, Saga University, Saga 840-8502 Japan (e-mail: kiguchi@ieee.org). T. Fukuda is with the Department of Micro System Engineering, Nagoya University, Aichi 464-8603 Japan (e-mail: fukuda@mein.nagoya-u.ac.jp). Digital Object Identifier 10.1109/TFUZZ.2004.832525
Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2004/8
Y1 - 2004/8
N2 - 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.
AB - 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.
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U2 - 10.1109/TFUZZ.2004.832525
DO - 10.1109/TFUZZ.2004.832525
M3 - Article
AN - SCOPUS:4344606548
SN - 1063-6706
VL - 12
SP - 481
EP - 490
JO - IEEE Transactions on Fuzzy Systems
JF - IEEE Transactions on Fuzzy Systems
IS - 4
ER -