Bereitschaftspotential modeling by DBNM and its application to BCI

  • Authors:

  • Shino Takata;Toshimasa Yamazaki;Maiko Sakamoto;Takahiro Yamanoi;Kenichi Kamijo

  • Affiliations:

  • Kyushu Institute of Technology, Japan;Kyushu Institute of Technology, Japan;Kyushu Institute of Technology, Japan;Hokkai Gakuen University, Japan;NEC Green Innovation Research Labs, Japan

  • Venue:
  • HI'11 Proceedings of the 2011 international conference on Human interface and the management of information - Volume Part I
  • Year:
  • 2011

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Abstract

In this study, movement-related potentials (MRPs) including Bereitschaftspotential (BP) is modeled by a dynamic Bayesian network model (DBNM). The containing the MRPs BP are divided into the early BP, NS' (negative slope) and MP (motor potential) intervals, each of which is represented by a Bayesian network model (BNM). Each BNM is constructed using the results by equivalent current dipole source localization (ECDL) after independent component analysis (ICA), for single-trial EEGs recorded during the hand movement. Nodes in the BNM correspond to the brain sites where dipoles are located. Connecting with the three BNMs yields a DBNM. This model is used to discriminate between the left- and right-hand movements in a framework of single-trial-electroencephalogram (EEG)-based BCI.