0545531 - FGÚ 2022 RIV CH eng J - Článek v odborném periodiku
Skalický, D. - Koucký, V. - Hadraba, Daniel - Vítězník, M. - Dub, M. - Lopot, F.
Detection of Respiratory Phases in a Breath Sound and Their Subsequent Utilization in a Diagnosis.
Applied Sciences-Basel. Roč. 11, č. 14 (2021), č. článku 6535. ISSN 2076-3417. E-ISSN 2076-3417
Grant CEP: GA MŠMT(CZ) LM2018129
Institucionální podpora: RVO:67985823
Klíčová slova: respiratory sounds * respiratory sounds * signal processing * filtering * analysis * respiratory phases
Obor OECD: Medical laboratory technology (including laboratory samples analysis
Impakt faktor: 2.838, rok: 2021
Způsob publikování: Open access
https://www.mdpi.com/2076-3417/11/14/6535

Detection of lung sounds and their propagation is a powerful tool for analysing the behaviour of the respiratory system. A common approach to detect the respiratory sounds is lung auscultation, however, this method has significant limitations including low sensitivity of human ear or ambient background noise. This article targets the major limitations of lung auscultation and presents a new approach to analyse the respiratory sounds and visualise them together with the respiratory phases. The respiratory sounds from 41 patients were recorded and filtered to eliminate the ambient noise and noise artefacts. The filtered signal is processed to identify the respiratory phases. The article also contains an approach for removing the noise that is very difficult to filter but the removal is crucial for identifying the respiratory phases. Finally, the respiratory phases are overlaid with the frequency spectrum which simplifies the orientation in the recording and additionally offers the information on the inter-individual ratio of the inhalation and exhalation phases. Such interpretation provides a powerful tool for further analysis of lung sounds, simplifythe diagnosis of various types of respiratory tract dysfunctions, and returns data which are comparable among the patients.
Trvalý link: http://hdl.handle.net/11104/0322220