Detecting Breathing and Snoring Episodes Using a Wireless Tracheal Sensor-A Feasibility Study.

Area of Science:

• Biomedical Engineering
• Sleep Medicine
• Acoustic Signal Processing

Background:

• Sleep-disordered breathing (SDB) presents significant clinical and social challenges.
• There is a need for accessible tools to facilitate SDB screening and diagnosis.

Purpose of the Study:

• To evaluate the sensitivity and specificity of a novel wireless acoustic system for detecting sleep breathing and snoring episodes.

Main Methods:

• Development and implementation of a wireless acoustic sensor integrated with a mobile application.
• Utilized spectral thresholding and heuristics for breathing episode segmentation and classification.
• System validation using 1520 manually labeled sleep episodes from 40 whole-night recordings of 16 healthy subjects.

Main Results:

• The system achieved 88.8% accuracy in differentiating normal breathing from snoring.
• A high specificity of 95% was reported, suitable for screening purposes.

Conclusions:

• The wireless system offers a practical, cost-effective alternative to traditional sleep studies.
• Enables repetitive, personalized, and reliable sleep data collection for enhanced sleep monitoring and research.