Abstrakt
Around 300 million people all over the world suffer from asthma [1]. This disease affects all ages and patients have primarily difficult breathing with wheezing in respiratory sounds, cough and feeling of constricted chest.
Therefore their physical activity is strongly limited [2]. For better treatment and relieving the disease symptoms the early diagnosis of the disease is needed.
For asthma (and other pulmonary diseases) diagnosing, we have some reliable methods: spirometry, measuring of peaks of expiratory velocity or measuring of bronchial reactivity. Unfortunately, these methods have their limits: They are not reliable for badly collaboration patients like infants to 3 years old, because these patients can't provide operations required for the diagnosis method (e.g. maximal inhalation and expiration).
In this case, the standard diagnosing methods can't be used and therefore it is necessary to develop other diagnosis method without need for difficult cooperation of these patients. One of the most probably working usable principles is observing changes in the breath sound of ill person and detection of wheezing and other sounds which are the typical manifestations of the disease [3].
These typical phenomena can be detected by auscultation or by observing changes in frequency spectra of breath sound recording, which is created by harmonic analysis. This method could be more sensitive and without need patient's collaboration.