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Related Concept Videos

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Related Experiment Video

Updated: Jun 3, 2026

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
02:09

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Published on: April 12, 2024

An Interpretable Multidimensional Acoustic Physiology Map for COPD Using Digital Lung Sounds.

İhsan Topaloğlu1, Çağrı Atasoy1, Aylin Bayram1

  • 1Department of Pulmonology, Faculty of Medicine, Kafkas University, Kars, Turkey.

Chronic Obstructive Pulmonary Diseases (Miami, Fla.)
|June 1, 2026
PubMed
Summary
This summary is machine-generated.

A new acoustic physiology map using four digital lung sound indices helps differentiate healthy individuals from those with stable chronic obstructive pulmonary disease (COPD) or COPD exacerbation, aiding clinical interpretation.

Keywords:
COPDacoustic indicedigital auscultationlung sound analysismachine learning

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Area of Science:

  • Pulmonary Medicine
  • Acoustic Analysis
  • Biomedical Engineering

Background:

  • Clinical interpretation of lung sound analysis for chronic obstructive pulmonary disease (COPD) can be challenging.
  • Digital lung sound analysis offers potential for capturing COPD-related physiology.
  • A multidimensional acoustic physiology map was developed using four key indices.

Purpose of the Study:

  • To develop and evaluate a multidimensional acoustic physiology map for differentiating COPD states.
  • To assess the clinical interpretability of digital lung sound indices.

Main Methods:

  • A retrospective study analyzed 1,403 lung sound recordings from 235 adults (Healthy, Stable COPD, COPD exacerbation).
  • Four acoustic indices were measured: median respiratory frequency (MRF), long-term energy index (LTEI), subharmonic index (SubH), and harmonicity deviation index (HDI).
  • Statistical analyses included Kruskal-Wallis, Dunn post-hoc tests, principal component analysis (PCA), and permutational multivariate analysis of variance.

Main Results:

  • Significant group differences were found for MRF, SubH, and HDI (P < 0.0001).
  • MRF and SubH distinguished Stable COPD from Healthy and COPD exacerbation groups.
  • HDI primarily separated COPD exacerbation from Healthy and Stable COPD groups.

Conclusions:

  • Complementary acoustic indices reflect distinct aspects of COPD sound generation and transmission.
  • The proposed acoustic map offers an interpretable framework for digital auscultation phenotyping.
  • While standalone performance was limited, the map shows potential for future composite scoring in COPD management.