An Adaptive Approach for Task-Driven BCI Calibration

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Abstract

One of the most significant obstacles for the every­day use of systems based on Brain­Computer Inter­faces (BCIs) is the tediousness of calibration. Successful improvements on calibration, particularly the time needed and the user­experience, have been made with, e.g., transfer learning, gamification, and task estimation [1, 2, 3]. In
this work, we present an adaptive approach to BCI systems’ calibration with a model that evaluates if more calibration is needed. We inspect the model in its simplest form to showcase its versatility.
Original languageEnglish
Publication statusPublished - 2021 Jun
EventBCI meeting 2021 - Virtual
Duration: 2021 Jun 72021 Jun 9
https://bcisociety.org/bci-meeting/

Conference

ConferenceBCI meeting 2021
Period2021/06/072021/06/09
Internet address

Subject classification (UKÄ)

  • Control Engineering

Keywords

  • BCI
  • Calibration
  • EEG
  • brain-computer interface

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