This section focuses on respiratory physiology, signal acquisition, processing, and clinical applications. It begins with an overview of respiratory system structure and function (Chapter 4.1), followed by the characterization of respiratory signals such as spirometry, plethysmography, inductance plethysmography, and multimodal approaches (Chapter 4.2). Signal processing techniques (Chapter 4.3) address breathing rate detection, variability analysis, abnormality detection, real-time monitoring, and advanced algorithms incorporating machine learning. Applications span filtering of respiratory signals, artifact removal, and classification for clinical insight. The section concludes with clinical applications (Chapter 4.4), including critical care and emergency monitoring, sleep medicine, perioperative care, and telemedicine, highlighting predictive analytics and remote monitoring. Together, these chapters emphasize the diagnostic and therapeutic importance of respiratory signal analysis in both hospital and home settings.