Abstract
We analysed respiration sounds of individual asthmatic patients, in the scope of the development of a method for computerized recognition of the degree of airway obstruction. Respiration sounds were recorded during laboratory sessions of histamine-provoked airway obstruction. We applied an interpolation technique using supervised artificial neural networks to investigate the optimal frequency band required for studying tracheal asthmatic lung sounds. The optimal band was found to be 100–2300 Hz. The forced expiratory volume in 1 s (FEV1) and the respiratory resistance parameter Rrs(4) were used to describe the degree of airway obstruction that is associated with the lung sounds. By comparing the results obtained with the two parameters, we found that for parametrization of the associated degree of airway obstruction respiratory resistance measurements are preferable over forced expiratory volume measurements.
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