This book describes breath signal processing technologies and their
applications in medical sample classification and diagnosis. First, it
provides a comprehensive introduction to breath signal acquisition
methods, based on different kinds of chemical sensors, together with the
optimized selection and fusion acquisition scheme. It then presents
preprocessing techniques, such as drift removing and feature extraction
methods, and uses case studies to explore the classification methods.
Lastly it discusses promising research directions and potential medical
applications of computerized breath diagnosis. It is a valuable
interdisciplinary resource for researchers, professionals and
postgraduate students working in various fields, including breath
diagnosis, signal processing, pattern recognition, and biometrics.