Respiratory Rate

Respiratory rate (RR), a crucial vital sign reflecting overall health, is the focus of intense research aiming to develop accurate and convenient monitoring methods. Current efforts concentrate on non-contact and continuous RR estimation using diverse data sources (e.g., photoplethysmography (PPG), radar, speech, video) and advanced machine learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and support vector machines (SVMs). These advancements hold significant promise for improving healthcare, particularly in remote patient monitoring, early disease detection, and personalized medicine by enabling continuous, unobtrusive, and cost-effective RR assessment.