Sleep Diagnostics and Monitoring Technology in Obstructive Sleep Apnea

Area of Science:

• Neurology
• Sleep Medicine
• Biomedical Engineering

Background:

• Obstructive sleep apnea (OSA) is prevalent and often underdiagnosed, especially in patients with neurological conditions.
• In-laboratory polysomnography is the gold standard for OSA diagnosis but faces accessibility and cost limitations.
• Home sleep apnea testing (HSAT) provides a validated alternative for diagnosing OSA in suitable patients.

Purpose of the Study:

• To guide neurologists on modern OSA diagnostic approaches.
• To detail the role and limitations of HSAT in clinical practice.
• To explore integrating wearable and noncontact technologies for improved OSA diagnosis and management.

Main Methods:

• Review of advancements in HSAT, including type III monitors, wearable sensors (wristbands, smart rings), and noncontact systems (radar, acoustic).
• Analysis of FDA-cleared software-as-a-medical-device platforms utilizing AI and multisignal integration for sleep parameter estimation.
• Discussion of the clinical utility, accuracy, and validation requirements for these emerging technologies.

Main Results:

• New HSAT technologies enhance diagnostic accessibility, particularly for patients unable to undergo polysomnography.
• Wearable and nearable devices offer expanded, scalable diagnostic options with varying accuracy and validation.
• AI-driven platforms are increasingly used for sleep parameter estimation, improving efficiency.

Conclusions:

• Neurologists are crucial in identifying high-risk patients, selecting appropriate diagnostic tests, and interpreting results considering limitations like pulse oximetry bias.
• Wearable and nearable technologies expand OSA diagnostic capabilities but necessitate further validation for equitable and reliable use.
• Modern continuous positive airway pressure (CPAP) platforms facilitate remote monitoring and management, improving patient care.