Literature DB >> 21097364

Acoustics based assessment of respiratory diseases using GMM classification.

P Mayorga1, C Druzgalski, R L Morelos, O H Gonzalez, J Vidales.   

Abstract

The focus of this paper is to present a method utilizing lung sounds for a quantitative assessment of patient health as it relates to respiratory disorders. In order to accomplish this, applicable traditional techniques within the speech processing domain were utilized to evaluate lung sounds obtained with a digital stethoscope. Traditional methods utilized in the evaluation of asthma involve auscultation and spirometry, but utilization of more sensitive electronic stethoscopes, which are currently available, and application of quantitative signal analysis methods offer opportunities of improved diagnosis. In particular we propose an acoustic evaluation methodology based on the Gaussian Mixed Models (GMM) which should assist in broader analysis, identification, and diagnosis of asthma based on the frequency domain analysis of wheezing and crackles.

Entities:  

Mesh:

Year:  2010        PMID: 21097364     DOI: 10.1109/IEMBS.2010.5628092

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  7 in total

Review 1.  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

2.  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

3.  Using K-Nearest Neighbor Classification to Diagnose Abnormal Lung Sounds.

Authors:  Chin-Hsing Chen; Wen-Tzeng Huang; Tan-Hsu Tan; Cheng-Chun Chang; Yuan-Jen Chang
Journal:  Sensors (Basel)       Date:  2015-06-04       Impact factor: 3.576

Review 4.  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

5.  Detection of Pneumonia Infection by Using Deep Learning on a Mobile Platform.

Authors:  Alhazmi Lamia; Alassery Fawaz
Journal:  Comput Intell Neurosci       Date:  2022-07-30

6.  A comparative study of the SVM and K-nn machine learning algorithms for the diagnosis of respiratory pathologies using pulmonary acoustic signals.

Authors:  Rajkumar Palaniappan; Kenneth Sundaraj; Sebastian Sundaraj
Journal:  BMC Bioinformatics       Date:  2014-06-27       Impact factor: 3.169

7.  Wheezing Sound Separation Based on Informed Inter-Segment Non-Negative Matrix Partial Co-Factorization.

Authors:  Juan De La Torre Cruz; Francisco Jesús Cañadas Quesada; Nicolás Ruiz Reyes; Pedro Vera Candeas; Julio José Carabias Orti
Journal:  Sensors (Basel)       Date:  2020-05-08       Impact factor: 3.576

  7 in total

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