Analysis and Classification for Single-Trial EEG Induced by Sequential Finger Movements.
Annu Int Conf IEEE Eng Med Biol Soc
; 2019: 4541-4544, 2019 Jul.
Article
en En
| MEDLINE
| ID: mdl-31946875
ABSTRACT
In recent years, motor imagery-based BCIs (MI-BCIs) controlled various external devices successfully, which have great potential in neurological rehabilitation. In this paper, we designed a paradigm of sequential finger movements and utilized spatial filters for feature extraction to classify single-trial electroencephalography (EEG) induced by finger movements of left and right hand. Ten healthy subjects participated the experiment. The analysis of EEG patterns showed significant contralateral dominance. We investigated how data length affected the classification accuracy. The classification accuracy was improved with the increase of the keystrokes in one trial, and the results were 87.42%, 91.21%, 93.08% and 93.59% corresponding to single keystroke, two keystrokes, three keystrokes and four keystrokes. This study would be helpful to improve the decoding efficiency and optimize the encoding method of motor-related EEG information.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Electroencefalografía
/
Interfaces Cerebro-Computador
/
Movimiento
Límite:
Humans
Idioma:
En
Revista:
Annu Int Conf IEEE Eng Med Biol Soc
Año:
2019
Tipo del documento:
Article