Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is a prevalent sleep disorder characterized by repeated interruptions of breathing during sleep, posing significant health risks. Current research focuses on developing accurate and accessible diagnostic tools, moving beyond the cumbersome gold standard of polysomnography. This involves exploring machine learning and deep learning models, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), applied to various data sources including snoring sounds, thermal imaging, radar, smartphone sensors, and even Wi-Fi signals. Improved diagnostic methods hold the potential to significantly enhance early detection, personalized treatment, and ultimately, improve patient outcomes and reduce healthcare costs associated with OSA.