Machine Learning-based Sleep Staging in Sleep Apnea Patients Using a Single Mandibular Movement Signal.
(2021) American Journal of Respiratory and Critical Care Medicine — Vol. 204, n° 10, p. 1227-1231 (2021)
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- Authors
Martinot, Jean-Benoît 
- Abstract
- (en) TO THE EDITOR : We all sleep, and sleep patterns and architecture influence our health and wellbeing. At present, the gold standard method for recording detailed sleep patterns to detect and monitor sleep disorders is in-laboratory overnight polysomnography (PSG), requiring specialized equipment and trained staff. This is no longer feasible in view of the size of the population with suspected sleep disorders, and especially in the coronavirus disease (COVID-19) era. [...]
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Citations
Le-Dong, N.-N., Martinot, J.-B., Coumans, N., Cuthbert, V., Tamisier, R., Bailly, S., & Pépin, J.-L. (2021). Machine Learning-based Sleep Staging in Sleep Apnea Patients Using a Single Mandibular Movement Signal. American Journal of Respiratory and Critical Care Medicine, 204(10), 1227-1231. https://doi.org/10.1164/rccm.202103-0680LE (Original work published 2021)