Editorial: Long Term User Training and Preparation to Succeed in a Closed -Loop BCI Competition

Gernot Muller-Putz, Damien Coyle, Fabien Lotte, Jing Jin, David Steyri

Research output: Contribution to journalEditorialpeer-review

1 Citation (Scopus)
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Computer Interfaces (BCIs) have been researched now for about 30 years. However, even
still,much of the work done in the lab environment is seldomapplied within the targeted end-users,
for example, people with severe motor disabilities.
The main goal of the research community should be to finally bring the BCI into a state in
which the end-users can profit and gain independence and quality of life. One possibility to push
the field into practical applications is driven by initiatives such as CYBATHLON [initiated by ETH
Zurich (Riener, 2016)] and other competitions. Such a competition challenges research institutions
and industry to demonstrate their developments in real-world scenarios and push the boundaries
of research.
In the BCI Race, at CYBATHLON (Novak et al., 2017), end-users are the pilots and they control
an avatar in a race against other pilots, by using a multi-class BCI. This competition and others are
enormously demanding to the developers, as the BCI system must work properly at the time of the
competition, out of the lab in a foreign environment, with spectators around, noise and without
second chances.
In China, a BCI competition was firstly organized by Tsinghua University in 2010. Since 2017,
the BCI competition has been organized by China Electronics Society as part of World Robotics
Conference. Thousands of users participate every year. This BCI competition consists of two parts,
a user competition and an algorithm competition. Winners of the user competition compete then
in the algorithm competition to test the performance of algorithms which were uploaded by BCI
research teams. Through these BCI competitions, a large amount of BCI data for further research
has been obtained, which has been used to promote the progress of BCI algorithms. In the near
future, these data will be published online for BCI researchers all over the world.
Another extremely important factor, of course, is the preparation of the team for the
competition. In particular, the end-user pilot should be trained to produce stable and accurate
mental states that produce consistent brain oscillations to control the BCI, even in a potentially
stressful environment such as in the CYBATHLON race arena.
Original languageEnglish
Article number869700
Pages (from-to)1-2
Number of pages2
JournalFrontiers in Human Neuroscience
Publication statusPublished (in print/issue) - 24 Mar 2022


  • brain computer interface
  • electroencephalogram
  • Transfer Learning
  • user learning
  • user-centered training
  • closed-loop learning
  • transfer learning
  • Brain-Computer Interface


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