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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Detalhes bibliográficos
Publicado no:Sci Rep
Main Authors: 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: Artigo
Idioma:Inglês
Publicado em: Nature Publishing Group UK 2021
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7794504/
https://ncbi.nlm.nih.gov/pubmed/33420133
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-79217-x
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