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Related Experiment Videos

Wheezing Lung Sounds Analysis with adaptive local trigonometric transform

E Ademovic1, J C Pesquet, G Charbonneau

  • 1Laboratoire des Signaux et Systèmes, CNRS/Univ. Paris-Sud and GdR-PRC ISIS, ESE, Gif sur Yvette, France. ademovic@lss.supelec.fr

Technology and Health Care : Official Journal of the European Society for Engineering and Medicine
|October 1, 1998
PubMed
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This study applies Adaptive Local Trigonometric Decomposition (ALTD) to analyze lung sounds, improving the detection of wheezes associated with Chronic Obstructive Pulmonary Diseases (COPD). The findings enhance patient monitoring and pharmacological research through advanced time-frequency analysis.

Area of Science:

  • Pulmonary Medicine
  • Biomedical Signal Processing
  • Medical Acoustics

Background:

  • Wheezes are abnormal respiratory sounds linked to Chronic Obstructive Pulmonary Diseases (COPD).
  • Analysis of lung sounds is crucial for patient monitoring and pharmacological studies.
  • Traditional analysis methods struggle with the complex, event-driven nature of respiratory sounds.

Purpose of the Study:

  • To investigate the application of Adaptive Local Trigonometric Decomposition (ALTD) for lung sound analysis.
  • To optimize ALTD parameterization for the specific detection of wheezing phenomena.
  • To enhance the time-frequency representation of respiratory signals.

Main Methods:

  • Utilized Adaptive Local Trigonometric Decomposition (ALTD) for signal analysis.

Related Experiment Videos

  • Focused on time-frequency domain representation of lung sounds.
  • Studied ALTD parameterization for detecting wheezing events.

    • Main Results:

    • ALTD provides an optimal time-frequency representation of lung sounds.
    • The method demonstrates potential for improved detection of wheezing phenomena.
    • Adapted lattice in the time-frequency domain enhances signal analysis.

    Conclusions:

    • Adaptive Local Trigonometric Decomposition is a promising technique for lung sound analysis.
    • ALTD parameterization can be effectively utilized for wheeze detection in COPD.
    • This approach offers advancements in respiratory sound analysis for clinical applications.