Sleep classification from wrist-worn accelerometer data using random forests

Accurate and low-cost sleep measurement tools are needed in both clinical and epidemiological research. To this end, wearable accelerometers are widely used as they are both low in price and provide reasonably accurate estimates of movement. Techniques to classify sleep from the high-resolution acce...

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Detalles Bibliográficos
Autores principales: Sundararajan, Kalaivani, Georgievska, Sonja, te Lindert, Bart H. W., Gehrman, Philip R., Ramautar, Jennifer, Mazzotti, Diego R., Sabia, Séverine, Weedon, Michael N., van Someren, Eus J. W., Ridder, Lars, Wang, Jian, van Hees, Vincent T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794504/
https://www.ncbi.nlm.nih.gov/pubmed/33420133
http://dx.doi.org/10.1038/s41598-020-79217-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794504/
https://www.ncbi.nlm.nih.gov/pubmed/33420133
http://dx.doi.org/10.1038/s41598-020-79217-x

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