Literature DB >> 19163231

Lung sound analysis for wheeze episode detection.

Abhishek Jain1, Jithendra Vepa.   

Abstract

Listening and interpreting lung sounds by a stethoscope had been an important component of screening and diagnosing lung diseases. However this practice has always been vulnerable to poor audibility, inter-observer variations (between different physicians) and poor reproducibility. Thus computerized analysis of lung sounds for objective diagnosis of lung diseases is seen as a probable aid. In this paper we aim at automatic analysis of lung sounds for wheeze episode detection and quantification. The proposed algorithm integrates and analyses the set of parameters based on ATS (American Thoracic Society) definition of wheezes. It is very robust, computationally simple and yielded sensitivity of 84% and specificity of 86%.

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Year:  2008        PMID: 19163231     DOI: 10.1109/IEMBS.2008.4649728

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

1.  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

2.  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

Review 3.  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

4.  Distance-Based Detection of Cough, Wheeze, and Breath Sounds on Wearable Devices.

Authors:  Bing Xue; Wen Shi; Sanjay H Chotirmall; Vivian Ci Ai Koh; Yi Yang Ang; Rex Xiao Tan; Wee Ser
Journal:  Sensors (Basel)       Date:  2022-03-10       Impact factor: 3.576

  4 in total

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