Joan S. Tunubalaa

Sleep apnea detection from respiratory sounds using time–Frequency features and neural networks 

A lightweight deep learning model that detects apnea events using a single acoustic channel is proposed, demonstrating that respiratory sounds contain sufficient information for reliable apnea detection and validating their potential as a non-invasive, low-cost biomarker.