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Separation and Classification of Crackles and Bronchial Breath Sounds from Normal Breath Sounds Using Gaussian Mixture Model

  • Ali Haider
  • M. Daniyal Ashraf
  • M. Usama Azhar
  • Syed Osama Maruf
  • Mehdi Naqvi
  • Sajid Gul Khawaja
  • M. Usman Akram
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8835)

Abstract

A computer aided diagnostic system capable of analyzing respiratory sounds can be very helpful in detection of pneumonia, asthma and tuberculosis as the Respiratory sound signal carries information about the underlying physiology of the lungs and is used to detect presence of adventitious lung sounds which are an indication of disease. Respiratory sound analysis helps in distinguishing normal respiratory sounds from abnormal respiratory sounds and this can be used to accurately diagnose respiratory diseases as is done by a medical specialist via auscultation. This process has subjective nature and that is why simple auscultation cannot be relied upon.In this paper we present a novel method for automated detection of crackles and bronchial breath sounds which when coupled together indicate presence and severity of Pneumonia. The proposed system consists of four modules i.e., pre-processing in which noise is filtered out, followed by feature extraction. The proposed system then performs classification to separate crackles and bronchial breath sounds from normal breath sounds.

Keywords

Positive Predictive Value Gaussian Mixture Model Wavelet Packet Breath Sound Lung Sound 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ali Haider
    • 1
  • M. Daniyal Ashraf
    • 1
  • M. Usama Azhar
    • 1
  • Syed Osama Maruf
    • 1
  • Mehdi Naqvi
    • 1
  • Sajid Gul Khawaja
    • 1
  • M. Usman Akram
    • 1
  1. 1.College of Electrical and Mechanical EngineeringNational University of Sciences and TechnologyPakistan

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