Open AccessArtificial Intelligence Analysis of Mandibular Movements Enables Accurate Detection of Phasic Sleep Bruxism in OSA Patients: A Pilot Study
Author(s) -
Jean-Benoît Martinot,
NhatNam LeDong,
Valérie Cuthbert,
Stéphane Denison,
David Gozal,
Gilles Lavigne,
JeanLouis Pépin
Publication year - 2021
Publication title -
nature and science of sleep
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.715
H-Index - 34
ISSN - 1179-1608
DOI - 10.2147/nss.s320664
Subject(s) - medicine , receiver operating characteristic , polysomnography , sleep bruxism , masticatory force , chin , confidence interval , electromyography , physical medicine and rehabilitation , apnea , orthodontics , anatomy
Sleep bruxism (SBx) activity is classically identified by capturing masseter and/or temporalis masticatory muscles electromyographic activity (EMG-MMA) during in-laboratory polysomnography (PSG). We aimed to identify stereotypical mandibular jaw movements (MJM) in patients with SBx and to develop rhythmic masticatory muscles activities (RMMA) automatic detection using an artificial intelligence (AI) based approach.