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Machine Learning–based Sleep Staging in Patients with Sleep Apnea Using a Single Mandibular Movement Signal

Nhat-Nam Le-Dong, Jean-Benoit Martinot, Nathalie Coumans, Valérie Cuthbert, Renaud Tamisier, Sébastien Bailly, Jean-Louis Pépin

2021American Journal of Respiratory and Critical Care Medicine37 citationsDOIOpen Access PDF

Abstract

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. [...]

Topics & Concepts

MedicinePolysomnographySleep (system call)Sleep apneaPopulationGold standard (test)Physical medicine and rehabilitationSleep StagesSleep apnea syndromesObstructive sleep apneaApneaSleep disorderRapid eye movement sleepEye movementElectromyographyAudiologyBreathingDiseaseNon-rapid eye movement sleepSlow-wave sleepPhysical therapySleep studyObstructive Sleep Apnea ResearchSleep and related disordersEEG and Brain-Computer Interfaces
Machine Learning–based Sleep Staging in Patients with Sleep Apnea Using a Single Mandibular Movement Signal | Litcius