NIH Reporter #1R03EB037909-01

Advancing Wakefulness Screening of Sleep Apnea Disorder through Breathing Sound Analysis and Hardware Optimization

The award supports the development of an improved, non-invasive sleep apnea screening tool using breathing sound analysis and hardware optimization to enable early detection and better accessibility, especially for underserved populations.

Description

This project aims to enhance a wakefulness-based sleep apnea screening tool that uses breathing sound analysis. The tool offers a non-invasive, accessible screening method, particularly for populations with limited access to sleep studies. The project has three aims: refine the algorithm by reducing the influence of anthropometric factors and incorporating intra-subject variance using machine learning; identify acoustic features that predict sleep metrics such as the apnea-hypopnea index; develop custom hardware and a microphone chamber for improved sound recording, creating a portable, cost-effective, and user-friendly device. The long-term goal is to provide an accessible screening tool for early detection of sleep apnea, especially in underserved populations and surgical patients, to reduce diagnostic costs and improve early intervention.

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