Performance comparison of machine learning techniques in sleep scoring based on wavelet features and neighboring component analysis

INTRODUCTION: Sleep scoring is an important step in the treatment of sleep disorders. Manual annotation of sleep stages is time-consuming and experience-relevant and, therefore, needs to be done using machine learning techniques. METHODS: Sleep-EDF polysomnography was used in this study as a dataset...

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Detalles Bibliográficos
Autores principales: Alizadeh Savareh, Behrouz, Bashiri, Azadeh, Behmanesh, Ali, Meftahi, Gholam Hossein, Hatef, Boshra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2018
Materias:
Bioinformatics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6064207/
https://www.ncbi.nlm.nih.gov/pubmed/30065866
http://dx.doi.org/10.7717/peerj.5247

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6064207/
https://www.ncbi.nlm.nih.gov/pubmed/30065866
http://dx.doi.org/10.7717/peerj.5247

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