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Automatic Control of Reactive Brain Computer Interfaces

Tufvesson, Pex LU orcid and Heskebeck, Frida LU orcid (2023)
Abstract
This article discusses practical and theoretical aspects of real-time brain computer interface control methods based on Bayesian statistics. We investigate and improve the performance of automatic control and feedback algorithms of a reactive brain computer interface based on a visual oddball paradigm for faster statistical convergence. We introduce transfer learning using Gaussian mixture models, enabling a ready-to-use setup.
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Working paper/Preprint
publication status
published
subject
pages
32 pages
publisher
arXiv.org
DOI
10.48550/arXiv.2310.07408
project
Optimizing the Next Generation Brain Computer Interfaces using Cloud Computing
language
English
LU publication?
yes
id
71f728df-d61f-4b2c-9cc6-c8be683c75b6
date added to LUP
2023-10-12 14:18:04
date last changed
2025-09-17 09:51:46
@misc{71f728df-d61f-4b2c-9cc6-c8be683c75b6,
  abstract     = {{This article discusses practical and theoretical aspects of real-time brain computer interface control methods based on Bayesian statistics. We investigate and improve the performance of automatic control and feedback algorithms of a reactive brain computer interface based on a visual oddball paradigm for faster statistical convergence. We introduce transfer learning using Gaussian mixture models, enabling a ready-to-use setup.}},
  author       = {{Tufvesson, Pex and Heskebeck, Frida}},
  language     = {{eng}},
  month        = {{10}},
  note         = {{Preprint}},
  publisher    = {{arXiv.org}},
  title        = {{Automatic Control of Reactive Brain Computer Interfaces}},
  url          = {{http://dx.doi.org/10.48550/arXiv.2310.07408}},
  doi          = {{10.48550/arXiv.2310.07408}},
  year         = {{2023}},
}