Shallow convolutional network excel for classifying motor imagery EEG in BCI applications

Many studies applying Brain-Computer Interfaces (BCIs) based on Motor Imagery (MI) tasks for rehabilitation have demonstrated the important role of detecting the Event-Related Desynchronization (ERD) to recognize the user’s motor intention. Nowadays, the development of MI-based BCI approaches withou...

Full description

Autores:
milanés hermosilla, daily
Trujillo Codorniú, Rafael
López Baracaldo, René
Sagaro Zamora, Roberto
Delisle-Rodriguez, Denis
Llosas Albuerne, Yolanda
Núñez Alvarez, José Ricardo
Tipo de recurso:
Article of journal
Fecha de publicación:
2021
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/8475
Acceso en línea:
https://hdl.handle.net/11323/8475
https://repositorio.cuc.edu.co/
Palabra clave:
Brain-computer interface
EEG
Motor imagery
Shallow convolutional neural networks
Rights
openAccess
License
CC0 1.0 Universal