Reference : Does Facemask Impact Diagnostic During Pulmonary Auscultation?
Scientific congresses and symposiums : Paper published in a journal
Human health sciences : Multidisciplinary, general & others
Human health sciences : Cardiovascular & respiratory systems
Engineering, computing & technology : Multidisciplinary, general & others
http://hdl.handle.net/2268/265725
Does Facemask Impact Diagnostic During Pulmonary Auscultation?
English
Uyttendaele, Vincent mailto [Université de Liège - ULiège > > GIGA In silico - Model-based therap., Critic. Care Basic Sc. >]
GUIOT, Julien mailto [Centre Hospitalier Universitaire de Liège - CHU > Département de médecine interne > Service de pneumologie - allergologie >]
Chase, J. Geoffrey [> >]
Desaive, Thomas mailto [Université de Liège - ULiège > Département d'astrophys., géophysique et océanographie (AGO) > Thermodynamique des phénomènes irréversibles >]
2021
IFAC-PapersOnLine
Elsevier
54
15
11th IFAC Symposium on Biological and Medical Systems BMS 2021
1-580
Yes (verified by ORBi)
International
2405-8963
Kidlington
United Kingdom
11th IFAC Symposium on Biological and Medical Systems BMS 2021
19-22 Septembre 2021
[en] Lung Sounds ; Breath Sounds ; Pulmonary Auscultation ; Universal Masking ; Facemasks ; Spectrogram
[en] Facemasks have been widely used in hospitals, especially since the emergence of the coronavirus 2019 (COVID-19) pandemic, often severely affecting respiratory functions. Masks protect patients from contagious airborne transmission, and are thus more specifically important for chronic respiratory disease (CRD) patients. However, masks also increase air resistance and thus work of breathing, which may impact pulmonary auscultation and diagnostic acuity, the primary respiratory examination. This study is the first to assess the impact of facemasks on clinical auscultation diagnostic.

Lung sounds from 29 patients were digitally recorded using an electronic stethoscope. For each patient, one recording was taken wearing a surgical mask and one without. Recorded signals were segmented in breath cycles using an autocorrelation algorithm. In total, 87 breath cycles were identified from sounds with mask, and 82 without mask. Time-frequency analysis of the signals was used to extract comparison features such as peak frequency, median frequency, band power, or spectral integration.

All the features extracted in frequency content, its evolution, or power did not significantly differ between respiratory cycles with or without mask. This early stage study thus suggests minor impact on clinical diagnostic outcomes in pulmonary auscultation. However, further analysis is necessary such as on adventitious sounds characteristics differences with or without mask, to determine if facemask could lead to no discernible diagnostic outcome in clinical practice.
GIGA - In Silico Medicine
Researchers ; Professionals
http://hdl.handle.net/2268/265725
10.1016/j.ifacol.2021.10.254

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