Detection of squawks in respiratory sounds of mechanically ventilated COVID-19 patients

• Main Author: Rocha, Bruno Machado
• Publication Date: 2021
• Other Authors: Pessoa, Diogo, Cheimariotis, Grigorios-Aris, Kaimakamis, Evangelos, Kotoulas, Serafeim-Chrysovalantis, Tzimou, Myrto, Maglaveras, Nicos, Marques, Alda, Carvalho, Paulo de, Paiva, Rui Pedro
• Format: Article
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/10773/33588
• topic: Respiratory Sounds; Audio Signal Processing; Intensive Care

Mechanically ventilated patients typically exhibit abnormal respiratory sounds. Squawks are short inspiratory adventitious sounds that may occur in patients with pneumonia, such as COVID-19 patients. In this work we devised a method for squawk detection in mechanically ventilated patients by developing algorithms for respiratory cycle estimation, squawk candidate identification, feature extraction, and clustering. The best classifier reached an F1 of 0.48 at the sound file level and an F1 of 0.66 at the recording session level. These preliminary results are promising, as they were obtained in noisy environments. This method will give health professionals a new feature to assess the potential deterioration of critically ill patients.