Cough or cough epochs may be an important and persistent symptom in many respiratory diseases requiring both a continuous and objective observation. The research presented in this paper is aimed to assess a blind data-based classification between 'spontaneous' and 'voluntary' human cough on individual sound samples. Cough sounds were registered in the free acoustic field on 3 pathological and 9 healthy non-smoking subjects, all aged between 20 and 30. Each sound is represented by the normalized power spectral density (PSD). Different transformations of the cough PSD-vector are chosen as input-features to the classification algorithm. An experimental error rate comparison between different neural and fuzzy classification networks is performed. All evaluated algorithms used the Euclidean metric. This resulted in a correct class-discrimination between 'spontaneous' and 'voluntary' cough for 96% of the cough database.

Index Terms. Artificial intelligence; Neural networks; Fuzzy reasoning; Expert system; Sound analysis; Cough