Literature DB >> 14723508

Time-frequency detection and analysis of wheezes during forced exhalation.

Antoni Homs-Corbera1, José Antonio Fiz, José Morera, Raimon Jané.   

Abstract

The objective of the present work was to detect and analyze wheezes by means of a highly sensitive time-frequency algorithm. Automatic measurements were compared with clinical auscultation for forced exhalation segments from 1.2 to 0 liters/second (l/s). Sensitivities between 100% and 71%, as a function of flow level related to wheezing segments detection, were achieved. Time-frequency wheeze parameters were measured for the flow range from 1.2 to 0.2 l/s. Wheezes were detected in both analyzed groups; asthmatics (N = 16) and control subjects (N = 15). Significant differences between groups were found for the mean number of wheezes detected at basal condition (p = 0.0003). Frequency parameter differences were also significant (0.0112 < p < 0.0307). All these parameters were also studied after applying a bronchodilator drug (Terbutaline). Significant differences between patient groups were found when studying the changes in the number of wheezes for each patient (p = 0.0195). Finally, limited bandwidth parameters, which measure the bronchodilator response, were also studied.

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Year:  2004        PMID: 14723508     DOI: 10.1109/TBME.2003.820359

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  14 in total

1.  Signal feature extraction by multi-scale PCA and its application to respiratory sound classification.

Authors:  Shengkun Xie; Feng Jin; Sridhar Krishnan; Farook Sattar
Journal:  Med Biol Eng Comput       Date:  2012-04-01       Impact factor: 2.602

2.  Applying cybernetic technology to diagnose human pulmonary sounds.

Authors:  Mei-Yung Chen; Cheng-Han Chou
Journal:  J Med Syst       Date:  2014-05-31       Impact factor: 4.460

Review 3.  Acoustic Methods for Pulmonary Diagnosis.

Authors:  Adam Rao; Emily Huynh; Thomas J Royston; Aaron Kornblith; Shuvo Roy
Journal:  IEEE Rev Biomed Eng       Date:  2018-10-29

4.  A survey on automated wheeze detection systems for asthmatic patients.

Authors:  Syamimi Mardiah Shaharum; Kenneth Sundaraj; Rajkumar Palaniappan
Journal:  Bosn J Basic Med Sci       Date:  2012-11       Impact factor: 3.363

5.  Analysis of respiratory sounds: state of the art.

Authors:  Sandra Reichert; Raymond Gass; Christian Brandt; Emmanuel Andrès
Journal:  Clin Med Circ Respirat Pulm Med       Date:  2008-05-16

6.  Soft stethoscope for detecting asthma wheeze in young children.

Authors:  Chun Yu; Tzu-Hsiu Tsai; Shi-Ing Huang; Chii-Wann Lin
Journal:  Sensors (Basel)       Date:  2013-06-06       Impact factor: 3.576

7.  An FPGA-based rapid wheezing detection system.

Authors:  Bor-Shing Lin; Tian-Shiue Yen
Journal:  Int J Environ Res Public Health       Date:  2014-01-29       Impact factor: 3.390

8.  Novel approach to continuous adventitious respiratory sound analysis for the assessment of bronchodilator response.

Authors:  Manuel Lozano-García; José Antonio Fiz; Carlos Martínez-Rivera; Aurora Torrents; Juan Ruiz-Manzano; Raimon Jané
Journal:  PLoS One       Date:  2017-02-08       Impact factor: 3.240

Review 9.  Automatic adventitious respiratory sound analysis: A systematic review.

Authors:  Renard Xaviero Adhi Pramono; Stuart Bowyer; Esther Rodriguez-Villegas
Journal:  PLoS One       Date:  2017-05-26       Impact factor: 3.240

10.  Low-power wearable respiratory sound sensing.

Authors:  Dinko Oletic; Bruno Arsenali; Vedran Bilas
Journal:  Sensors (Basel)       Date:  2014-04-09       Impact factor: 3.576

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