A study on EMG-based human motion prediction for power assist exoskeletons

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

A power-assist exoskeleton robot, which is directly attached to the user's body and assist the motion in accordance with the user's intension, is one of the most effective human assist robots for the physically weak persons. Many studies on power-assist robots have been carried out to help the motion of physically weak persons such as disabled, injured, and/or elderly persons. EMG-based control (i.e., control based on the skin surface electromyogram (EMG) signals of the user) is one of the most effective control methods for the power-assist robots, since EMG signals of user's muscles directly reflect the user's motion intension. However, the EMG-based control is not easy to be realized because of many reasons. The paper presents an effective human motion prediction method from the EMG signals using a neuro-fuzzy technique for the control of power-assist exoskeleton robots.

Original languageEnglish
Title of host publicationProceedings of the 2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007
Pages190-195
Number of pages6
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007 - Jacksonville, FL, United States
Duration: Jun 20 2007Jun 23 2007

Publication series

NameProceedings of the 2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007

Other

Other2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007
Country/TerritoryUnited States
CityJacksonville, FL
Period6/20/076/23/07

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'A study on EMG-based human motion prediction for power assist exoskeletons'. Together they form a unique fingerprint.

Cite this