Real-Time MEG-Based Brain-Geminoid Control Using Single-trial SVM Classification

Abdelkader Nasreddine Belkacem, Hiroshi Ishiguro, Shuichi Nishio, Masayuki Hirata, Takafumi Suzuki

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

6 Citations (Scopus)

Abstract

In this paper, we presents a novel non-invasive brain-Geminoid control system by using single-trial classification of bimanual movements to achieving a noninvasive brain-computer interface (BCI) with many control dimensions and easily interact with an outdoor complex environment in real-time. Two BCI-naive subjects performed or imagined performing 4 movements of bimanual hand during the measurement of magnetic fields to control a Geminoid HI-2 (humanoid robot) through a multidimensional BCI. We applied a nonlinear support vector machine (SVM) to classify the 4 bimanual hand movements using 114 magnetoencephalography (MEG) sensors over the sensorimotor cortex. The mean classification accuracy of a 2-class decoding was suitable for real-time brain-Geminoid control application, with classification accuracies equivalent to those obtained in precedent BCI studies involving uni-manual movements. Moreover, our results demonstrated that decoding bimanual hand movements in real-time using the amplitudes of the event-related magnetic fields is very promising to implement multidimensional-control based BCIs.

Original languageEnglish
Title of host publicationICARM 2018 - 2018 3rd International Conference on Advanced Robotics and Mechatronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages679-684
Number of pages6
ISBN (Electronic)9781538670668
DOIs
Publication statusPublished - Jan 11 2019
Externally publishedYes
Event3rd IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2018 - Singapore, Singapore
Duration: Jul 18 2018Jul 20 2018

Publication series

NameICARM 2018 - 2018 3rd International Conference on Advanced Robotics and Mechatronics

Conference

Conference3rd IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2018
Country/TerritorySingapore
CitySingapore
Period7/18/187/20/18

Keywords

  • Bimanual hand movements
  • Brain-computer interface (BCI)
  • Geminoid HI-2
  • Magnetoencephalographic (MEG)
  • Support vector machine (SVM)

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering
  • Control and Optimization

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