Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 1 de 1
Filtrar
Más filtros











Base de datos
Intervalo de año de publicación
1.
Annu Int Conf IEEE Eng Med Biol Soc ; 2015: 1765-8, 2015 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-26736620

RESUMEN

Intention recognition through decoding brain activity could lead to a powerful and independent Brain-Computer-Interface (BCI) allowing for intuitive control of devices like robots. A common strategy for realizing such a system is the motor imagery (MI) BCI using electroencephalography (EEG). Changing to invasive recordings like electrocorticography (ECoG) allows extracting very robust features and easy introduction of an idle state, which might simplify the mental task and allow the subject to focus on the environment. Especially for multi-channel recordings like ECoG, common spatial patterns (CSP) provide a powerful tool for feature optimization and dimensionality reduction. This work focuses on an invasive and independent MI BCI that allows triggering from an idle state, and therefore facilitates tele-operation of a humanoid robot. The task was to lift a can with the robot's hand. One subject participated and reached 95.4 % mean online accuracy after six runs of 40 trials. To our knowledge, this is the first online experiment with a MI BCI using CSPs from ECoG signals.


Asunto(s)
Interfaces Cerebro-Computador , Electrocorticografía , Mano , Imaginación , Robótica , Anciano , Electroencefalografía , Diseño de Equipo , Femenino , Humanos , Modelos Teóricos
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA