Asthma diagnosis based on respiratory dynamic using sparse representation based-classifier

Asthma is a chronic disease which requires being diagnosed early to start treating. A modified Sparse Representation based-Classifier (SRC) is introduced which is capable to classify all datasets such as asthma diagnosis dataset. In particular, both inter-breathing intervals (IBI) and volume of respiratory patterns and features which extracted based on those signals incorporated to diagnose asthma. The discrimination capability of the classifiers are evaluated using the classification parameters such as: sensitivity, specificity, accuracy and etc. This classification technique is used to diagnose asthma with respiratory patterns dynamics.