AIMC Topic: Sleep Apnea, Obstructive

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Belun Sleep Platform versus in-lab polysomnography for obstructive sleep apnea diagnosis.

Sleep & breathing = Schlaf & Atmung
OBJECTIVE: We aimed to compare the Belun Sleep Platform (BSP), an artificial intelligence-driven home sleep testing device, with polysomnography (PSG) for diagnosing obstructive sleep apnea. The BSP analyzes oxygen saturation, heart rate, and acceler...

Diagnostic accuracy of artificial intelligence for obstructive sleep apnea detection: a systematic review.

BMC medical informatics and decision making
BACKGROUND: Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder. Misdiagnosis might lead to several systemic conditions, including hypertension, vascular damage, and cognitive impairment. The gold-standard diagnostic tool for OSA is po...

Evaluating changes in hypoglossal nerve stimulator use over time and long-term adherence.

Sleep & breathing = Schlaf & Atmung
PURPOSE: Evaluate patient phenotypes and longitudinal patterns of hypoglossal nerve stimulator (HGNS) use and identify predictors of long-term HGNS adherence.

Incorporating the STOP-BANG questionnaire improves prediction of cardiovascular events during hospitalization after myocardial infarction.

Scientific reports
Obstructive sleep apnea (OSA) may impact outcomes in acute coronary syndrome (ACS) patients. The Global Registry of Acute Coronary Events (GRACE) score assesses cardiovascular risk post-ACS. This study evaluated whether incorporating the STOP-BANG sc...

Apnea detection using wrist actigraphy in patients with heterogeneous sleep disorders.

Scientific reports
Obstructive sleep apnea (OSA) and related hypoxia are well-established cardiovascular and neurocognitive risk factors. Current multi-sensor diagnostic approaches are intrusive and prone to misdiagnosis when simplified. This study introduces an enhanc...

Robust performances of a nocturnal long-term ECG algorithm for the evaluation of sleep apnea syndrome: A pilot study.

PloS one
Obstructive sleep apnea-hypopnea syndrome (OSAHS) is one of the most common sleep disorders affecting nearly one billion of the global adult population, making it a major public health issue. Even if in-lab polysomnography (PSG) remains the gold stan...

Artificial intelligence in obstructive sleep apnea: Transforming diagnosis and management.

Respiratory medicine
Obstructive Sleep Apnea (OSA) is a common disorder characterized by repeated airway collapse during sleep, leading to significant health risks. The traditional diagnosis of OSA through polysomnography is resource-intensive, leading to delays in diagn...

Separating obstructive and central respiratory events during sleep using breathing sounds: Utilizing transfer learning on deep convolutional networks.

Sleep medicine
Sleep apnea diagnosis relies on polysomnography (PSG), which is resource-intensive and requires manual analysis to differentiate obstructive sleep apnea (OSA) from central sleep apnea (CSA). Existing portable devices, while valuable in detecting slee...

GraphSleepFormer: a multi-modal graph neural network for sleep staging in OSA patients.

Journal of neural engineering
Obstructive sleep apnea (OSA) is a prevalent sleep disorder. Accurate sleep staging is one of the prerequisites in the study of sleep-related disorders and the evaluation of sleep quality. We introduce a novel GraphSleepFormer (GSF) network designed ...

Robotic beds for the treatment of positional obstructive sleep apnea - A randomized cross-over pilot trial.

Sleep medicine
BACKGROUND: Interventions leading to avoidance of supine position and thus reducing the likelihood of upper airway collapse during sleep are a treatment approach for positional obstructive sleep apnea (POSA). The aim of this randomized cross-over tri...