Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Validated method for automatic detection of lung sound crackles.

T Kaisla1, A Sovijärvi, P Piirilä

  • 1Department of Technical Physics, Helsinki University of Technology, Finland.

Medical & Biological Engineering & Computing
|September 1, 1991
PubMed
Summary

An automatic method for detecting crackles in lung sounds shows high accuracy for diagnosing pulmonary diseases like fibrosing alveolitis and bronchiectasis. This reliable tool offers objective analysis for clinical and research use.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Steam-assisted respiratory muscle training may improve sleep quality in mild-to-moderate obstructive sleep apnea: a pilot polysomnography study.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine·2026
Same author

Effects of steam-assisted respiratory muscle training on sleep apnoea symptoms and pulmonary function in men and women: a pilot study.

Sleep & breathing = Schlaf & Atmung·2025
Same author

Association of breathing sound spectra with glottal dimensions in exercise-induced vocal cord dysfunction.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery·2017
Same author

Physical activity, cardiorespiratory fitness, and metabolic outcomes in monozygotic twin pairs discordant for body mass index.

Scandinavian journal of medicine & science in sports·2017
Same author

Patient with multiple acyl-CoA dehydrogenation deficiency disease and FLAD1 mutations benefits from riboflavin therapy.

Neuromuscular disorders : NMD·2017
Same author

Allergic rhinoconjunctivitis doubles the risk for incident asthma--results from a population study in Helsinki, Finland.

Respiratory medicine·2011

Area of Science:

  • Pulmonary Medicine
  • Biomedical Engineering
  • Signal Processing

Background:

  • Crackling lung sounds are indicators of various pulmonary diseases, reflecting disease severity.
  • Accurate detection of these sounds is crucial for diagnosis and monitoring.
  • Current methods may lack objectivity and speed for large-scale analysis.

Purpose of the Study:

  • To develop and validate an automatic method for detecting crackles in lung sounds.
  • To assess the method's reliability and accuracy in patients with fibrosing alveolitis and bronchiectasis.
  • To provide a tool for rapid and objective analysis of crackling lung sounds.

Main Methods:

  • Developed an automatic crackle detection method analyzing spectral stationarity of lung sounds.

Related Experiment Videos

  • Validated the method on 20 adult patients (10 with fibrosing alveolitis, 10 with bronchiectasis).
  • Compared automatic detection counts with expert observer counts from time-expanded waveforms.

    • Main Results:

    • The automatic method achieved 89% sensitivity and 88% positive predictivity for fibrosing alveolitis.
    • For bronchiectasis, sensitivity was 80% and positive predictivity was 83%.
    • High linear correlation coefficients (0.86 for FA, 0.93 for BE) were found between automatic and expert counts.

    Conclusions:

    • The developed automatic crackle detection method is reliable for clinical and scientific applications.
    • It enables rapid, objective analysis, particularly useful for large datasets.
    • This technology can aid in the diagnosis and management of pulmonary diseases characterized by crackles.