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Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection
In the clinic, the wheezing sound is usually considered as an indicator symptom to reflect the degree of airway obstruction. The auscultation approach is the most common way to diagnose wheezing sounds, but it subjectively depends on the experience of the physician. Several previous studies attempte...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5298744/ https://www.ncbi.nlm.nih.gov/pubmed/28106747 http://dx.doi.org/10.3390/s17010171 |
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author | Li, Shih-Hong Lin, Bor-Shing Tsai, Chen-Han Yang, Cheng-Ta Lin, Bor-Shyh |
author_facet | Li, Shih-Hong Lin, Bor-Shing Tsai, Chen-Han Yang, Cheng-Ta Lin, Bor-Shyh |
author_sort | Li, Shih-Hong |
collection | PubMed |
description | In the clinic, the wheezing sound is usually considered as an indicator symptom to reflect the degree of airway obstruction. The auscultation approach is the most common way to diagnose wheezing sounds, but it subjectively depends on the experience of the physician. Several previous studies attempted to extract the features of breathing sounds to detect wheezing sounds automatically. However, there is still a lack of suitable monitoring systems for real-time wheeze detection in daily life. In this study, a wearable and wireless breathing sound monitoring system for real-time wheeze detection was proposed. Moreover, a breathing sounds analysis algorithm was designed to continuously extract and analyze the features of breathing sounds to provide the objectively quantitative information of breathing sounds to professional physicians. Here, normalized spectral integration (NSI) was also designed and applied in wheeze detection. The proposed algorithm required only short-term data of breathing sounds and lower computational complexity to perform real-time wheeze detection, and is suitable to be implemented in a commercial portable device, which contains relatively low computing power and memory. From the experimental results, the proposed system could provide good performance on wheeze detection exactly and might be a useful assisting tool for analysis of breathing sounds in clinical diagnosis. |
format | Online Article Text |
id | pubmed-5298744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-52987442017-02-10 Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection Li, Shih-Hong Lin, Bor-Shing Tsai, Chen-Han Yang, Cheng-Ta Lin, Bor-Shyh Sensors (Basel) Article In the clinic, the wheezing sound is usually considered as an indicator symptom to reflect the degree of airway obstruction. The auscultation approach is the most common way to diagnose wheezing sounds, but it subjectively depends on the experience of the physician. Several previous studies attempted to extract the features of breathing sounds to detect wheezing sounds automatically. However, there is still a lack of suitable monitoring systems for real-time wheeze detection in daily life. In this study, a wearable and wireless breathing sound monitoring system for real-time wheeze detection was proposed. Moreover, a breathing sounds analysis algorithm was designed to continuously extract and analyze the features of breathing sounds to provide the objectively quantitative information of breathing sounds to professional physicians. Here, normalized spectral integration (NSI) was also designed and applied in wheeze detection. The proposed algorithm required only short-term data of breathing sounds and lower computational complexity to perform real-time wheeze detection, and is suitable to be implemented in a commercial portable device, which contains relatively low computing power and memory. From the experimental results, the proposed system could provide good performance on wheeze detection exactly and might be a useful assisting tool for analysis of breathing sounds in clinical diagnosis. MDPI 2017-01-17 /pmc/articles/PMC5298744/ /pubmed/28106747 http://dx.doi.org/10.3390/s17010171 Text en © 2017 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Shih-Hong Lin, Bor-Shing Tsai, Chen-Han Yang, Cheng-Ta Lin, Bor-Shyh Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection |
title | Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection |
title_full | Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection |
title_fullStr | Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection |
title_full_unstemmed | Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection |
title_short | Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection |
title_sort | design of wearable breathing sound monitoring system for real-time wheeze detection |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5298744/ https://www.ncbi.nlm.nih.gov/pubmed/28106747 http://dx.doi.org/10.3390/s17010171 |
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