Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/33588
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 |
URI: | http://hdl.handle.net/10773/33588 |
DOI: | 10.1109/EMBC46164.2021.9630734 |
ISSN: | 2375-7477 |
Appears in Collections: | IBIMED - Artigos ESSUA - Artigos Lab3R - Artigos |
Files in This Item:
File | Description | Size | Format | |
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2021_Rocha_Detection of squawks in respiratory sounds_IEEE Eng in Medicine.pdf | 1.89 MB | Adobe PDF | View/Open |
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