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...
- 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