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      Broad-Band Visually Evoked Potentials: Re(con)volution in Brain-Computer Interfacing

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      Creators
      Thielen, J.
      Farquhar, J.D.R.
      Desain, P.W.M.
      Date of Archiving
      2018
      Archive
      Radboud Data Repository
      Data archive handle
      https://hdl.handle.net/11633/di.dcc.DSC_2018.00047_553
      Related publications
      Broad-band visually evoked potentials: Re(con)volution in brain-computer interfacing  
      Publication type
      Dataset
      Access level
      Restricted access
      Please use this identifier to cite or link to this item: https://hdl.handle.net/2066/203789   https://hdl.handle.net/2066/203789
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      Organization
      SW OZ DCC CO
      SW OZ DCC AI
      Audience(s)
      Life sciences
      Languages used
      English
      Key words
      Brain Computer Interface
      Abstract
      Brain-Computer Interfaces (BCIs) allow users to control devices and communicate by using brain activity only. BCIs based on broad-band visual stimulation can outperform BCIs using other stimulation paradigms. Visual stimulation with pseudo-random bit-sequences evokes specific Broad-Band Visually Evoked Potentials (BBVEPs) that can be reliably used in BCI for high-speed communication in speller applications. In this study, we reported a novel paradigm for a BBVEP-based BCI that utilised a generative framework to predict responses to broad-band stimulation sequences. In this study we designed a BBVEP-based BCI using modulated Gold codes to mark cells in a 6 x 6 visual speller BCI. We defined a linear generative model that decomposes full responses into overlapping single-flash responses. These single-flash responses are used to predict responses to novel stimulation sequences, which in turn serve as templates for classification. These predicted responses are proven to be well-suited as templates for a BBVEP-based BCI, thereby enabling communication and control by brain activity only.
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      • Datasets [1282]
      • Faculty of Social Sciences [27347]
       
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