A Novel Wheeze Detection Method for Wearable Monitoring Systems

Wheezy breath is a general sign for airway obstructive diseases like asthma and chronic obstructive pulmonary disease. This paper presents a novel wheeze detection method that can be used to detect and identify wheezes automatically. The proposed method exploits ``entropy" to describe the patte...

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Bibliographic Details
Published in2009 International Symposium on Intelligent Ubiquitous Computing and Education : 15-16 May 2009 pp. 331 - 334
Main Authors Jianmin Zhang, Wee Ser, Jufeng Yu, Zhang, T.T.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2009
Subjects
Biomedical monitoring
Computational complexity
Computerized monitoring
Condition monitoring
Diseases
Entropy
entropy based
Frequency
Hidden Markov models
Lungs
Signal processing
wearable
wheeze detection
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ISBN9780769536194
0769536190
DOI10.1109/IUCE.2009.66

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Summary:Wheezy breath is a general sign for airway obstructive diseases like asthma and chronic obstructive pulmonary disease. This paper presents a novel wheeze detection method that can be used to detect and identify wheezes automatically. The proposed method exploits ``entropy" to describe the pattern of the frequency spectrum of the wheezing signal and the wheeze identification can be conducted using only one or two entropy-based features. Therefore the proposed method has considerably reduced computational complexity and is able to operate with the low power consumption constraint under the wearable condition. The performance of the proposed method has been evaluated using lung sounds from patients and normal subjects under different Signal-to-Noise Ratio (SNR).
ISBN:9780769536194
0769536190
DOI:10.1109/IUCE.2009.66