Development of a motor imagery based brain-computer interface for humanoid robot control applications

Narendra Prakaksita, Chen Yun Kuo, Chung Hsien Kuo

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

21 Scopus citations

Abstract

This paper focuses on the developments of asynchronous motor imagery (MI) based brain-computer interfaces (BCIs) applications, signal processing and machine learning to provide some basic capabilities for consumer grade products. For the proposed MI detection technique, two channels of FC5 and FC6 according to 10-20 system over primary motor area are used to recognize 3 mental tasks of tongue, left hand and right hand movements. The amplitude features of EEG signals are extracted from power spectral analysis especially in mu rhythm (8-12 Hz) and low beta wave (12-16 Hz) bands. MI features were obtained from offline analysis, and then applied to neural network (NN) with particle swarm optimization (PSO). The classification paradigm then applied to real-time BCI for humanoid robot control applications in terms of recognized MI classes from subjects. According to the experiments of 45 trials for a healthy subject, the NN-based MI recognition accuracy with PSO is 91%.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE International Conference on Industrial Technology, ICIT 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1607-1613
Number of pages7
ISBN (Electronic)9781467380751
DOIs
StatePublished - 19 05 2016
Externally publishedYes
EventIEEE International Conference on Industrial Technology, ICIT 2016 - Taipei, Taiwan
Duration: 14 03 201617 03 2016

Publication series

NameProceedings of the IEEE International Conference on Industrial Technology
Volume2016-May

Conference

ConferenceIEEE International Conference on Industrial Technology, ICIT 2016
Country/TerritoryTaiwan
CityTaipei
Period14/03/1617/03/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • Brain-computer interfaces
  • EEG
  • motor imagery
  • neural network
  • particle swarm optimization

Fingerprint

Dive into the research topics of 'Development of a motor imagery based brain-computer interface for humanoid robot control applications'. Together they form a unique fingerprint.

Cite this