Massive online data annotation, crowdsourcing to generate high quality sleep spindle annotations from EEG data

Spindle event detection is a key component in analyzing human sleep. However, detection of these oscillatory patterns by experts is time consuming and costly. Automated detection algorithms are cost efficient and reproducible but require robust datasets to be trained and validated. Using the MODA (M...

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Detalles Bibliográficos
Autores principales: Lacourse, Karine, Yetton, Ben, Mednick, Sara, Warby, Simon C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Analysis
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305234/
https://www.ncbi.nlm.nih.gov/pubmed/32561751
http://dx.doi.org/10.1038/s41597-020-0533-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305234/
https://www.ncbi.nlm.nih.gov/pubmed/32561751
http://dx.doi.org/10.1038/s41597-020-0533-4

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