Información del artículo
Resumen
Las Interfaces Cerebro-Computador proporcionan un canal para enviar órdenes al mundo exterior haciendo uso de medidas electrofisiológicas de la actividad cerebral. En este artículo se presenta la combinación de un método de selección de características y un algoritmo de clasificación probabilístico para construir el modelo predictivo de la intención anticipada de movimiento voluntario de pacientes con temblor a partir de un solo ensayo. Los resultados obtenidos muestran una potencial de discriminación del 70%, una tasa de error aceptable (6.6%) y una rápida respuesta (cada 250ms), lo que indica que esta combinación es una buena base para la construcción de ICCs que no requieran entrenamiento del usuario de forma personalizada, asíncrona y adaptativa.
Palabras clave:
Interfaz Cerebro-Computador (ICC) asíncrona
señal electroencefalográfica
personalización
ritmos sensorimotores
minería de datos
adaptación
clasificación
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