Automatic sleep stages classification using EEG entropy features and unsupervised pattern analysis techniques
Sleep is a growing area of research interest in medicine and neuroscience. Actually, one major concern is to find a correlation between several physiologic variables and sleep stages. There is a scientific agreement on the characteristics of the five stages of human sleep, based on EEG analysis. Nev...
- Autores:
-
Rodríguez-Sotelo J.L.
Osorio-Forero A.
Jiménez-Rodríguez A.
Cuesta-Frau D.
Cirugeda-Roldán E.
Peluffo Ordoñez, Diego H.
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2014
- Institución:
- Universidad Cooperativa de Colombia
- Repositorio:
- Repositorio UCC
- Idioma:
- OAI Identifier:
- oai:repository.ucc.edu.co:20.500.12494/42807
- Acceso en línea:
- https://doi.org/10.5935/1678-9741.20140101
https://www.sciencedirect.com/science/article/abs/pii/S0109564112004034
https://hdl.handle.net/20.500.12494/42807
- Palabra clave:
- Clustering
Feature extraction
Feature selection
Q-a
Relevance analysis
Signal entropy
Sleep stages
- Rights
- closedAccess
- License
- http://purl.org/coar/access_right/c_14cb