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A kind of integrated serial algorithms for noise reduction and characteristics expanding in respiratory sound

The computer‑based lung respiratory sound analysis, which can provide more information about the condition of lung station, has achieved a great development in recent years. However, the external noise in respiratory sound signal is a large restriction to the further promotion of this technique. In...

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Detalles Bibliográficos
Autores principales: Meng, Fei, Wang, Yixuan, Shi, Yan, Zhao, Hongmei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743292/
https://www.ncbi.nlm.nih.gov/pubmed/31523193
http://dx.doi.org/10.7150/ijbs.33274
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author Meng, Fei
Wang, Yixuan
Shi, Yan
Zhao, Hongmei
author_facet Meng, Fei
Wang, Yixuan
Shi, Yan
Zhao, Hongmei
author_sort Meng, Fei
collection PubMed
description The computer‑based lung respiratory sound analysis, which can provide more information about the condition of lung station, has achieved a great development in recent years. However, the external noise in respiratory sound signal is a large restriction to the further promotion of this technique. In this paper, a kind of serial integrated de-noising algorithms which consist of a FIR band-pass filter and a modified wavelet filter and an adaptive filter, is proposed to suppress the noise in respiratory sound signals. The design of this kind of filter and its practical application are studied. The practical application in de-noise of the lung sound shows that this filter has a good de-noising effect and a good performance in outstanding the acoustic characteristics.
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spelling pubmed-67432922019-09-14 A kind of integrated serial algorithms for noise reduction and characteristics expanding in respiratory sound Meng, Fei Wang, Yixuan Shi, Yan Zhao, Hongmei Int J Biol Sci Research Paper The computer‑based lung respiratory sound analysis, which can provide more information about the condition of lung station, has achieved a great development in recent years. However, the external noise in respiratory sound signal is a large restriction to the further promotion of this technique. In this paper, a kind of serial integrated de-noising algorithms which consist of a FIR band-pass filter and a modified wavelet filter and an adaptive filter, is proposed to suppress the noise in respiratory sound signals. The design of this kind of filter and its practical application are studied. The practical application in de-noise of the lung sound shows that this filter has a good de-noising effect and a good performance in outstanding the acoustic characteristics. Ivyspring International Publisher 2019-07-21 /pmc/articles/PMC6743292/ /pubmed/31523193 http://dx.doi.org/10.7150/ijbs.33274 Text en © The author(s) This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
spellingShingle Research Paper
Meng, Fei
Wang, Yixuan
Shi, Yan
Zhao, Hongmei
A kind of integrated serial algorithms for noise reduction and characteristics expanding in respiratory sound
title A kind of integrated serial algorithms for noise reduction and characteristics expanding in respiratory sound
title_full A kind of integrated serial algorithms for noise reduction and characteristics expanding in respiratory sound
title_fullStr A kind of integrated serial algorithms for noise reduction and characteristics expanding in respiratory sound
title_full_unstemmed A kind of integrated serial algorithms for noise reduction and characteristics expanding in respiratory sound
title_short A kind of integrated serial algorithms for noise reduction and characteristics expanding in respiratory sound
title_sort kind of integrated serial algorithms for noise reduction and characteristics expanding in respiratory sound
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743292/
https://www.ncbi.nlm.nih.gov/pubmed/31523193
http://dx.doi.org/10.7150/ijbs.33274
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