To review technological advancements and classification methods for the diagnosis and monitoring of obstructive sleep apnea (OSA).
Approach:
Introduction: Discusses the prevalence of OSA, its health implications, and the role of wearable technology in monitoring vital signs.
Diagnostic Techniques: Examines in-lab polysomnography (PSG) and home sleep apnea testing (HSAT) as primary diagnostic methods, highlighting their limitations and the potential of IoT technologies.
Review Methodology: Describes the search methodology for selecting relevant studies and the criteria for inclusion and exclusion.
Key Findings:
Over 1 billion people worldwide are affected by sleep apnea, with significant underdiagnosis.
Wearable technologies are advancing, allowing for better monitoring of physiological parameters.
HSAT devices are expanding but do not fully replace PSG due to performance variability.
Integration of IoT technologies with respiratory systems can enhance OSA assessment accuracy.
Interpretation:
Limitations:
Current diagnostic methods like PSG and HSAT have limitations in robustness and patient comfort.
Challenges remain in developing small, low-cost, and reliable IoT devices for accurate diagnosis.
Conclusion:
The paper aims to provide a comprehensive overview of OSA diagnostics, integrating wearable technologies and real-time monitoring capabilities.
A cross-sectional metagenomic study found greater oral microbiome richness among adults with chronic rhinosinusitis, particularly nonallergic chronic rhinosinusitis, while associations with asthma, airway inflammation, and most lung-function measures were inconsistent.
