Observation, parametric modelling and classification of respiratory sounds
Başlık çevirisi mevcut değil.
- Tez No: 364445
- Danışmanlar: YRD. DOÇ. DR. YASEMİN P. KAHYA
- Tez Türü: Yüksek Lisans
- Konular: Biyomühendislik, Göğüs Hastalıkları, Bioengineering, Chest Diseases
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 1992
- Dil: İngilizce
- Üniversite: Boğaziçi Üniversitesi
- Enstitü: Biyo-Medikal Mühendislik Enstitüsü
- Ana Bilim Dalı: Biyomedikal Mühendisliği Ana Bilim Dalı
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 160
Özet
Özet yok.
Özet (Çeviri)
Auscultation is a widely used method in the diagnosis of pulmonary diseases and in the analysis of respiratory sounds. The characteristics of respiratory sounds show differences in pathological cases from normal cases. The object of this study is, to observe the characteristics of respiratory sounds in both cases, to analyse them in time and frequency domain and to distinguish a normal case from a pathological case. To achieve mentioned goals, respiratory sounds heard over the chest waH from the specific locations were recorded. The flow signal was also recorded by a flowmeter to synchronize on the inspiration and expiration phases, because the characteristics of respiratory sounds may change from phase to phase. An AR modeling was applied to obtain a parametric representation of the sounds. The analysis of respiratory sounds was performed after they were distinguished to inspiration and expiration phases. Mahalanobis distance measure, and minimum distance classification method is used to classify respiratory sounds into appropriate classes. Experiments showed that the suggested classifier can distinguish the normal case from a pathological case if and only if a large database of lung sounds is available. The classification method was also compared with Itakura distance measure and k-nearest neighbor classification method which was performed in a previous study. The abrupt changes (crackles) in the respiratory sound waveforms of pathological cases were observed and a new method is suggested to detect them because they have a special importance in the diagnosis of some pulmonary diseases.
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