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A novel SSVEP-Based brain-computer interface using joint frequency and space modulation

  • Zhenyu Wang
  • , Honglin Hu
  • , Xianfu Chen
  • , Ting Zhou
  • , Tianheng Xu
  • Chinese Academy of Sciences
  • ShanghaiTech University

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

Abstract

Traditional steady state visual evoked potential (SSVEP) based brain-computer interfaces (BCIs) encode visual targets mainly with different stimulation frequencies. However, as more and more visual targets are squeezed into the limited stimulation spectrum in order to improve the BCIs' communication rate, the distinguishability among the neighboring targets with adjacent stimulation frequencies is to certain extent compromised. To solve this problem, in this paper a novel joint modulation scheme is proposed for the SSVEP-based BCIs, In the new scheme, visual targets are jointly encoded with different frequencies and different spatial forms. In this way, better classification performance can be achieved, especially for the neighboring targets. A four-target prototype system is developed and tested. The validity of the proposed new system using joint modulation is verified.
Original languageEnglish
Title of host publicationIEEE INFOCOM 2020 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2020
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages906-911
ISBN (Electronic)978-1-7281-8695-5
DOIs
Publication statusPublished - Jul 2020
MoE publication typeA4 Article in a conference publication
Event2020 IEEE INFOCOM Conference on Computer Communications Workshops, INFOCOM WKSHPS 2020 - Toronto, Canada
Duration: 6 Jul 20209 Jul 2020

Conference

Conference2020 IEEE INFOCOM Conference on Computer Communications Workshops, INFOCOM WKSHPS 2020
Country/TerritoryCanada
CityToronto
Period6/07/209/07/20

Funding

The authors’ work was supported in part by the National Key Research and Development Program of China (No. 2018YFB1802300) and the Science and Technology Commission Foundation of Shanghai (Nos. 19511103102 and 18DZ1113302).

Keywords

  • BCI
  • EEG
  • FDMA
  • Higher communication rate
  • SDMA
  • SSVEP

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