EEG correlates of video game experience and user profile in motor-imagery-based brain–computer interaction

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F17%3A00096343" target="_blank" >RIV/00216224:14330/17:00096343 - isvavai.cz</a>
Result on the web
<a href="http://link.springer.com/article/10.1007/s00371-016-1304-2?no-access=true" target="_blank" >http://link.springer.com/article/10.1007/s00371-016-1304-2?no-access=true</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s00371-016-1304-2" target="_blank" >10.1007/s00371-016-1304-2</a>

Result language
angličtina
Original language name
EEG correlates of video game experience and user profile in motor-imagery-based brain–computer interaction
Original language description
Through the use of brain–computer interfaces (BCIs), neurogames have become increasingly more advanced by incorporating immersive virtual environments and 3D worlds. However, training both the user and the system requires long and repetitive trials resulting in fatigue and low performance. Moreover, many users are unable to voluntarily modulate the amplitude of their brain activity to control the neurofeedback loop. In this study, we are focusing on the effect that gaming experience has in brain activity modulation as an attempt to systematically identify the elements that contribute to high BCI control and to be utilized in neurogame design. Based on the current literature, we argue that experienced gamers could have better performance in BCI training due to enhanced sensorimotor learning derived from gaming. To investigate this, two experimental studies were conducted with 20 participants overall, undergoing 3 BCI sessions, resulting in 88 EEG datasets. Results indicate (a) an effect from both demographic and gaming experience data to the activity patterns of EEG rhythms, and (b) increased gaming experience might not increase significantly performance, but it could provide faster learning for ‘Hardcore’ gamers.
Czech name
—
Czech description
—

Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)