Wearable Sensors for Monitoring Abnormalities in Sleep-Related Breathing

Area of Science:

• Biomedical Engineering
• Sleep Medicine
• Wearable Technology

Background:

• Sleep-disordered breathing (SDB), including obstructive sleep apnea, is common and linked to serious health issues.
• Polysomnography (PSG) is the gold standard for SDB diagnosis but is costly and inconvenient.
• There is a need for accessible, user-friendly methods for SDB detection and monitoring.

Purpose of the Study:

• To review the progress of wearable sensors for monitoring sleep-related breathing abnormalities.
• To discuss sensing principles, designs, and applications of wearable respiratory monitoring.
• To identify limitations and opportunities for advancing wearable sleep monitoring technology.

Main Methods:

• Review of current literature on wearable sensors for sleep-related breathing abnormalities.
• Integration of diverse sensing modalities (mechanical, optical, acoustic, electrophysiological).
• Focus on capturing physiological parameters like oxygen saturation, airflow, and movement.

Main Results:

• Wearable sensors enable portable, noninvasive assessment of respiratory function in daily environments.
• AI-assisted analysis of data from integrated sensors can support SDB detection.
• Key limitations include motion artifacts, comfort, and multimodal data fusion challenges.

Conclusions:

• Wearable sensors show significant promise as alternatives to PSG for SDB monitoring.
• Further development is needed to overcome current limitations for widespread clinical adoption.
• Next-generation wearable sensors can facilitate accurate, efficient, and personalized sleep health management.