An Adaptive Approach for Task-Driven BCI Calibration

Research output: Contribution to conferenceAbstractpeer-review

70 Downloads (Pure)


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


ConferenceBCI meeting 2021
Internet address

Subject classification (UKÄ)

  • Control Engineering

Free keywords

  • BCI
  • Calibration
  • EEG
  • brain-computer interface


Dive into the research topics of 'An Adaptive Approach for Task-Driven BCI Calibration'. Together they form a unique fingerprint.

Cite this