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Title: Detection of squawks in respiratory sounds of mechanically ventilated COVID-19 patients
Author: Rocha, Bruno Machado
Pessoa, Diogo
Cheimariotis, Grigorios-Aris
Kaimakamis, Evangelos
Kotoulas, Serafeim-Chrysovalantis
Tzimou, Myrto
Maglaveras, Nicos
Marques, Alda
Carvalho, Paulo de
Paiva, Rui Pedro
Keywords: Respiratory Sounds
Audio Signal Processing
Intensive Care
Issue Date: 2021
Publisher: IEEE
Abstract: 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.
Peer review: yes
DOI: 10.1109/EMBC46164.2021.9630734
ISSN: 2375-7477
Appears in Collections:IBIMED - Artigos
ESSUA - Artigos
Lab3R - Artigos

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