Sleep Apnea

Sleep apnea, a sleep disorder characterized by pauses in breathing during sleep, is a significant health concern currently under intense investigation. Research focuses on developing accurate and accessible diagnostic tools, moving beyond the cumbersome gold-standard polysomnography towards non-contact methods like thermal imaging, radar, and even analysis of radio waves reflected off the body. These efforts leverage machine learning algorithms, including deep neural networks and automated machine learning pipelines, to analyze diverse data sources such as ECG signals, infrared video, and even facial features, aiming for improved diagnostic accuracy and broader accessibility. The development of more convenient and accurate diagnostic tools holds significant promise for improving the diagnosis and management of sleep apnea, impacting both clinical practice and public health.