Wheeze Detection Algorithm Based on Correlation-Coefficients Analysis
Summary :
Wheeze is a general sign for obstructive airway diseases whose clinical diagnosis mainly depends on auscultating or X-ray imaging with subjectivity or harm. Therefore, this paper introduces an automatic, noninvasive method to detect wheeze which consists of STFT decomposition, preprocessing of the spectrogram, correlation-coefficients calculating and duration determining. In particular, duration determining takes the Haas effect into account, which facilitates us to achieve a better determination. Simulation result shows that the sensibility (SE), the specificity (SP) and the accuracy (AC) are 88.57%, 97.78% and 93.75%, respectively, which indicates that this method could be an efficient way to detect wheeze.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E99-A No.3 pp.760-764
- Publication Date
- 2016/03/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E99.A.760
- Type of Manuscript
- LETTER
- Category
- Digital Signal Processing
Authors
Jiarui LI
Chinese Academy of Sciences,University of Chinese Academy of Sciences
Ying HONG
Chinese Academy of Sciences
Chengpeng HAO
Chinese Academy of Sciences
Keyword
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Jiarui LI, Ying HONG, Chengpeng HAO, "Wheeze Detection Algorithm Based on Correlation-Coefficients Analysis" in IEICE TRANSACTIONS on Fundamentals,
vol. E99-A, no. 3, pp. 760-764, March 2016, doi: 10.1587/transfun.E99.A.760.
Abstract: Wheeze is a general sign for obstructive airway diseases whose clinical diagnosis mainly depends on auscultating or X-ray imaging with subjectivity or harm. Therefore, this paper introduces an automatic, noninvasive method to detect wheeze which consists of STFT decomposition, preprocessing of the spectrogram, correlation-coefficients calculating and duration determining. In particular, duration determining takes the Haas effect into account, which facilitates us to achieve a better determination. Simulation result shows that the sensibility (SE), the specificity (SP) and the accuracy (AC) are 88.57%, 97.78% and 93.75%, respectively, which indicates that this method could be an efficient way to detect wheeze.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E99.A.760/_p
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@ARTICLE{e99-a_3_760,
author={Jiarui LI, Ying HONG, Chengpeng HAO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Wheeze Detection Algorithm Based on Correlation-Coefficients Analysis},
year={2016},
volume={E99-A},
number={3},
pages={760-764},
abstract={Wheeze is a general sign for obstructive airway diseases whose clinical diagnosis mainly depends on auscultating or X-ray imaging with subjectivity or harm. Therefore, this paper introduces an automatic, noninvasive method to detect wheeze which consists of STFT decomposition, preprocessing of the spectrogram, correlation-coefficients calculating and duration determining. In particular, duration determining takes the Haas effect into account, which facilitates us to achieve a better determination. Simulation result shows that the sensibility (SE), the specificity (SP) and the accuracy (AC) are 88.57%, 97.78% and 93.75%, respectively, which indicates that this method could be an efficient way to detect wheeze.},
keywords={},
doi={10.1587/transfun.E99.A.760},
ISSN={1745-1337},
month={March},}
Copy
TY - JOUR
TI - Wheeze Detection Algorithm Based on Correlation-Coefficients Analysis
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 760
EP - 764
AU - Jiarui LI
AU - Ying HONG
AU - Chengpeng HAO
PY - 2016
DO - 10.1587/transfun.E99.A.760
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E99-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2016
AB - Wheeze is a general sign for obstructive airway diseases whose clinical diagnosis mainly depends on auscultating or X-ray imaging with subjectivity or harm. Therefore, this paper introduces an automatic, noninvasive method to detect wheeze which consists of STFT decomposition, preprocessing of the spectrogram, correlation-coefficients calculating and duration determining. In particular, duration determining takes the Haas effect into account, which facilitates us to achieve a better determination. Simulation result shows that the sensibility (SE), the specificity (SP) and the accuracy (AC) are 88.57%, 97.78% and 93.75%, respectively, which indicates that this method could be an efficient way to detect wheeze.
ER -
English
