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Sensors 2017, 17(1), 171; doi:10.3390/s17010171

Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection

1
Department of Thoracic Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan 33305, Taiwan
2
Department of Computer Science and Information Engineering, National Taipei University, New Taipei City 23741, Taiwan
3
Institute of Imaging and Biomedical Photonics, National Chiao Tung University, Tainan 71150, Taiwan
4
Department of Thoracic Medicine, Chang Gung Memorial Hospital at Taoyuan, Taoyuan 33378, Taiwan
5
Department of Respiratory Therapy, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 13 November 2016 / Revised: 27 December 2016 / Accepted: 13 January 2017 / Published: 17 January 2017
(This article belongs to the Special Issue Wearable Biomedical Sensors)
View Full-Text   |   Download PDF [3373 KB, uploaded 17 January 2017]   |  

Abstract

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. View Full-Text
Keywords: airway obstruction; wheeze detection; short-term breathing sound; spectral integration airway obstruction; wheeze detection; short-term breathing sound; spectral integration
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MDPI and ACS Style

Li, S.-H.; Lin, B.-S.; Tsai, C.-H.; Yang, C.-T.; Lin, B.-S. Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection. Sensors 2017, 17, 171.

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