The Berlin Brain--Computer Interface: accurate performance from first-session in BCI-naïve subjects
| Autor: | Benjamin Blankertz, Gabriel Curio, Matthias Krauledat, F. Losch, Klaus-Robert Müller, Guido Dornhege |
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| Rok vydání: | 2008 |
| Předmět: |
Adult
Male Computer science Speech recognition medicine.medical_treatment Interface (computing) Movement Biomedical Engineering Electroencephalography Biofeedback Functional Laterality Pattern Recognition Automated User-Computer Interface Artificial Intelligence medicine Humans Learning Session (computer science) Man-Machine Systems Brain–computer interface Brain Mapping medicine.diagnostic_test Electromyography Foot Brain Biofeedback Psychology Signal Processing Computer-Assisted Electrooculography Neurophysiology Hand Pattern recognition (psychology) Imagination Evoked Potentials Visual Female Neurofeedback Psychomotor Performance |
| Zdroj: | IEEE transactions on bio-medical engineering. 55(10) |
| ISSN: | 1558-2531 |
| Popis: | The Berlin brain-computer interface (BBCI) project develops a noninvasive BCI system whose key features are: 1) the use of well-established motor competences as control paradigms; 2) high-dimensional features from multichannel EEG; and 3) advanced machine-learning techniques. Spatio-spectral changes of sensorimotor rhythms are used to discriminate imagined movements (left hand, right hand, and foot). A previous feedback study [M. Krauledat, K.-R. Muller, and G. Curio. (2007) The non-invasive Berlin brain-computer Interface: Fast acquisition of effective performance in untrained subjects. NeuroImage. [Online]. 37(2), pp. 539--550. Available: http://dx.doi.org/10.1016/j.neuroimage.2007.01.051] with ten subjects provided preliminary evidence that the BBCI system can be operated at high accuracy for subjects with less than five prior BCI exposures. Here, we demonstrate in a group of 14 fully BCI-naive subjects that 8 out of 14 BCI novices can perform at >84% accuracy in their very first BCI session, and a further four subjects at >70%. Thus, 12 out of 14 BCI-novices had significant above-chance level performances without any subject training even in the first session, as based on an optimized EEG analysis by advanced machine-learning algorithms. |
| Databáze: | OpenAIRE |
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