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EMG signal decoded based virtual artificial intelligence hand control system

  • Long Yu*
  • , Yanjuan Gen
  • , Dandan Tao
  • , Guodong Zhou
  • , Liang Chen
  • , Guanglin Li
  • , Lushen Wu
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

An electromyography (EMG) decoded based virtual artificial intelligence control system has been developed to quantify the performance of real-time control of a multifunctional myoelectric prosthesis. To develop this platform system, a three-dimensional upper limb was simulated by using Solidworks and then implemented into an integrated scene of virtual artificial limb, which was programmed in virtual reality modeling language (VRML) and performed through Simulink toolbox of the MATLAB. By decoding surface electromyography (sEMG) signals collected from arm muscle surface, the platform system can identify thesix classes of different arm and hand movements and control the virtual artificial limb and/or the physical arms simultaneously. The VR-based platform also provides a relaxant and enjoyable training environment for prosthesis-users in clinic.

Original languageEnglish
Title of host publicationComputational Materials Science, CMS 2011
Pages422-427
Number of pages6
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 International Conference on Computational Materials Science, CMS 2011 - Guangzhou, China
Duration: 17 Apr 201118 Apr 2011

Publication series

NameAdvanced Materials Research
Volume268-270
ISSN (Print)1022-6680

Conference

Conference2011 International Conference on Computational Materials Science, CMS 2011
Country/TerritoryChina
CityGuangzhou
Period17/04/1118/04/11

Keywords

  • Artificial intelligence
  • Electromyography
  • Multifunctional prosthesis control
  • Virtual reality technology

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