Respiratory sounds of pathological and healthy subjects were analyzed via autoregressive (AR) models with a view to construct a diagnostic aid based on auscultation. Using the AR vectors, two reference libraries, pathological and healthy, were built. ⋯ Performances of the classifiers were tested for different model orders. The best classification results were obtained for model order 6.
Department of Electrical Engineering, Boğaziçi University, Bebek, Istanbul, Turkey.
Comput. Biol. Med. 1994 Jan 1;24(1):67-76.
AbstractRespiratory sounds of pathological and healthy subjects were analyzed via autoregressive (AR) models with a view to construct a diagnostic aid based on auscultation. Using the AR vectors, two reference libraries, pathological and healthy, were built. Two classifiers, k-nearest neighbour (k-NN) classifier and a quadratic classifier, were designed and compared. Performances of the classifiers were tested for different model orders. The best classification results were obtained for model order 6.