Mandibular Movements are a Reliable Noninvasive Alternative to Esophageal Pressure for Measuring Respiratory Effort in Patients with Sleep Apnea Syndrome.

Purpose: Differentiation between obstructive and central apneas and hypopneas requires quantitative measurement of respiratory effort (RE) using esophageal pressure (PES), which is rarely implemented. This study investigated whether the sleep mandibular movements (MM) signal recorded with a tri-axial gyroscopic chin sensor (Sunrise, Namur, Belgium) is a reliable surrogate of PES in patients with suspected obstructive sleep apnea (OSA).

Patients And Methods: In-laboratory polysomnography (PSG) with PES and concurrent MM monitoring was performed.

Clinical validation of a mandibular movement signal based system for the diagnosis of pediatric sleep apnea.

Background: Given the high prevalence and risk for outcomes associated with pediatric obstructive sleep apnea (OSA), there is a need for simplified diagnostic approaches. A prospective study in 140 children undergoing in-laboratory polysomnography (PSG) evaluates the accuracy of a recently developed system (Sunrise) to estimate respiratory efforts by monitoring sleep mandibular movements (MM) for the diagnosis of OSA (Sunrise™).

Methods: Diagnosis and severity were defined by an obstructive apnea/hypopnea index (OAHI) ≥ 1 (mild), ≥ 5 (moderate), and ≥ 10 events/h (severe).

The key role of the mandible in modulating airflow amplitude during sleep.

Rationale: Mandibular position and motion during sleep rely on the balance between mandibular elevators and depressors. We hypothesized that vertical mandibular position (VMP) modulates airflow amplitude during sleep.

Methods: VMP, tidal nasal flow pressure (NFP) and concurrent surface electromyographic activity of the masseters (sEMG-m) were recorded and processed by a customized algorithm from 100 polysomnographic fragments including a micro-arousal (25 obstructive sleep apnea patients).

Assessment of Mandibular Movement Monitoring With Machine Learning Analysis for the Diagnosis of Obstructive Sleep Apnea.

Importance: Given the high prevalence of obstructive sleep apnea (OSA), there is a need for simpler and automated diagnostic approaches.

Objective: To evaluate whether mandibular movement (MM) monitoring during sleep coupled with an automated analysis by machine learning is appropriate for OSA diagnosis.

Design, Setting, And Participants: Diagnostic study of adults undergoing overnight in-laboratory polysomnography (PSG) as the reference method compared with simultaneous MM monitoring at a sleep clinic in an academic institution (Sleep Laboratory, Centre Hospitalier Universitaire Université Catholique de Louvain Namur Site Sainte-Elisabeth, Namur, Belgium).

Respiratory Mandibular Movement Signals Reliably Identify Obstructive Hypopnea Events During Sleep.

Accurate discrimination between obstructive and central hypopneas requires quantitative assessments of respiratory effort by esophageal pressure (OeP) measurements, which preclude widespread implementation in sleep medicine practice. Mandibular Movement (MM) signals are closely associated with diaphragmatic effort during sleep. We aimed at reliably detecting obstructive off central hypopneas events using MM statistical characteristics.

Mandibular Movement Analysis to Assess Efficacy of Oral Appliance Therapy in OSA.

Rationale: The respiratory effort index derived from vertical mandibular movements (MM-REI) is a potential marker of increased respiratory effort during sleep. We evaluated the effectiveness of mandibular advancement splint therapy using MM-REI, in comparison with the apnea-hypopnea index (AHI) and oxygen desaturation index (ODI).

Methods: Fifty-six subjects (median age, 47 years) with OSA treated with a custom mandibular advancement splint (Herbst appliance) were evaluated at the end of the titration procedure when snoring was reported absent by the sleep partner.

Mandibular Movements As Accurate Reporters of Respiratory Effort during Sleep: Validation against Diaphragmatic Electromyography.

Context: Mandibular movements (MM) are considered as reliable reporters of respiratory effort (RE) during sleep and sleep disordered breathing (SDB), but MM accuracy has never been validated against the gold standard diaphragmatic electromyography (EMG-d).

Objectives: To assess the degree of agreement between MM and EMG-d signals during different sleep stages and abnormal respiratory events.

Methods: Twenty-five consecutive adult patients with SDB were studied by polysomnography (PSG) that also included multipair esophageal diaphragm electromyography and a magnetometer to record MM.

Monitoring mandibular movements to detect Cheyne-Stokes Breathing.

Background: The patterns of mandibular movements (MM) during sleep can be used to identify increased respiratory effort periodic large-amplitude MM (LPM), and cortical arousals associated with "sharp" large-amplitude MM (SPM). We hypothesized that Cheyne Stokes breathing (CSB) may be identified by periodic abnormal MM patterns. The present study aims to evaluate prospectively the concordance between CSB detected by periodic MM and polysomnography (PSG) as gold-standard.

Mandibular position and movements: Suitability for diagnosis of sleep apnoea.

Background And Objective: Mandibular movements (MMs) and position during sleep reflect respiratory efforts related to increases in upper airway resistance and micro-arousals. The study objective was to assess whether MM identifies sleep-disordered breathing (SDB) in patients with moderate to high pre-test probability.

Methods: This was a prospective study of 87 consecutive patients referred for an in-laboratory sleep test.

Mandibular movements identify respiratory effort in pediatric obstructive sleep apnea.

Study Objectives: Obstructive sleep apnea-hypopnea (OAH) diagnosis in children is based on the quantification of flow and respiratory effort (RE). Pulse transit time (PTT) is one validated tool to recognize RE. Pattern analysis of mandibular movements (MM) might be an alternative method to detect RE.