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Are Online Co-adaptive Sensorimotor Rhythm Brain-Computer Interface Training Paradigms Effective?
- Source :
- CW
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- Operating a non-invasive electroencephalogram (EEG) based sensorimotor rhythm brain-computer interface (BCI) is a skill that typically requires extensive training. Lately, online co-adaptive feedback training approaches achieved promising results. Does this also mean that users can have meaningful BCI-based interactions after training? To answer this question an online study was conducted with 10 naive (first time) users. The users trained to gain BCI control by playing a Whack-A-Mole game for about 30 minutes. During this time BCI parameters were adapting to the users EEG patterns. The adaptation was then stopped and users continued playing the game with the trained BCI for another 20 minutes. Eight out of the ten users were able to control the BCI and play the game. These preliminary results seem to suggest that online co-adaptation is an effective way to gain BCI control.
- Subjects :
- medicine.diagnostic_test
InformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.,HCI)
Computer science
Interface (computing)
0206 medical engineering
Training (meteorology)
Online study
02 engineering and technology
Electroencephalography
020601 biomedical engineering
Eeg patterns
03 medical and health sciences
InformationSystems_MODELSANDPRINCIPLES
0302 clinical medicine
Sensorimotor rhythm
Human–computer interaction
medicine
Adaptation (computer science)
030217 neurology & neurosurgery
Brain–computer interface
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2018 International Conference on Cyberworlds (CW)
- Accession number :
- edsair.doi...........9ed40e40167d8a1947c87f7dd80daa82
- Full Text :
- https://doi.org/10.1109/cw.2018.00081