التفاصيل البيبلوغرافية
| العنوان: |
Integrating EEG and MEG Signals to Improve Motor Imagery Classification in Brain–Computer Interface. |
| المؤلفون: |
Corsi, Marie-Constance, Chavez, Mario, Schwartz, Denis, Hugueville, Laurent, Khambhati, Ankit N., Bassett, Danielle S., De Vico Fallani, Fabrizio |
| المصدر: |
International Journal of Neural Systems; Feb2019, Vol. 29 Issue 1, pN.PAG-N.PAG, 12p |
| مصطلحات موضوعية: |
BRAIN-computer interfaces, ELECTROENCEPHALOGRAPHY, MAGNETOENCEPHALOGRAPHY, MOTOR imagery (Cognition), MULTIMODAL user interfaces |
| مستخلص: |
We adopted a fusion approach that combines features from simultaneously recorded electroencephalogram (EEG) and magnetoencephalogram (MEG) signals to improve classification performances in motor imagery-based brain–computer interfaces (BCIs). We applied our approach to a group of 15 healthy subjects and found a significant classification performance enhancement as compared to standard single-modality approaches in the alpha and beta bands. Taken together, our findings demonstrate the advantage of considering multimodal approaches as complementary tools for improving the impact of noninvasive BCIs. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
