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 Concept Videos

Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

110
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
110
Heart Sounds01:15

Heart Sounds

2.0K
Heart sounds are generated by the turbulence in blood flow due to the closing of heart valves. These sounds are best perceived slightly away from the valves, where the blood flow disseminates the sound.
Auscultation is the process of listening to these internal body sounds using a stethoscope. The heart produces four types of sounds, but only two—S1 and S2—can usually be heard with a stethoscope.
S1, also known as the "lub" sound, is caused by the closure of atrioventricular (A-V)...
2.0K

You might also read

Related Articles

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

Sort by
Same author

Design and Control of a 1-DOF MRI Compatible Pneumatically Actuated Robot with Long Transmission Lines.

IEEE/ASME transactions on mechatronics : a joint publication of the IEEE Industrial Electronics Society and the ASME Dynamic Systems and Control Division·2011
Same author

Effect of oxidized low-density lipoprotein concentration polarization on human smooth muscle cells' proliferation, cycle, apoptosis and oxidized low-density lipoprotein uptake.

Journal of the Royal Society, Interface·2011
Same author

Acrolein hydrogenation on Pt(211) and Au(211) surfaces: a density functional theory study.

Physical chemistry chemical physics : PCCP·2011
Same author

Anhydrous proton-conducting membrane based on poly-2-vinylpyridinium dihydrogenphosphate for electrochemical applications.

The journal of physical chemistry. B·2011
Same author

Pharmacophore identification, virtual screening and biological evaluation of prenylated flavonoids derivatives as PKB/Akt1 inhibitors.

European journal of medicinal chemistry·2011
Same author

Metabolomic study of insomnia and intervention effects of Suanzaoren decoction using ultra-performance liquid-chromatography/electrospray-ionization synapt high-definition mass spectrometry.

Journal of pharmaceutical and biomedical analysis·2011

Related Experiment Video

Updated: Jul 18, 2025

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

544

Lung Sound Recognition Method Based on Multi-Resolution Interleaved Net and Time-Frequency Feature Enhancement.

Lukui Shi, Jingye Zhang, Bo Yang

    IEEE Journal of Biomedical and Health Informatics
    |August 23, 2023
    PubMed
    Summary

    Artificial intelligence aids lung disease diagnosis by analyzing lung sounds. A novel model improves accuracy by effectively processing time and frequency data, enhancing early detection and reducing healthcare burdens.

    More Related Videos

    Author Spotlight: Enhancing Diagnostic Strategies and Biomarker Development for Comprehensive Lung Function Analysis
    05:56

    Author Spotlight: Enhancing Diagnostic Strategies and Biomarker Development for Comprehensive Lung Function Analysis

    Published on: August 9, 2024

    1.3K
    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
    05:48

    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

    Published on: August 9, 2024

    1.5K

    Related Experiment Videos

    Last Updated: Jul 18, 2025

    Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
    10:44

    Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

    Published on: June 21, 2024

    544
    Author Spotlight: Enhancing Diagnostic Strategies and Biomarker Development for Comprehensive Lung Function Analysis
    05:56

    Author Spotlight: Enhancing Diagnostic Strategies and Biomarker Development for Comprehensive Lung Function Analysis

    Published on: August 9, 2024

    1.3K
    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
    05:48

    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

    Published on: August 9, 2024

    1.5K

    Area of Science:

    • Medical Technology
    • Artificial Intelligence
    • Pulmonology

    Background:

    • Rising rates of lung diseases due to air pollution and aging populations necessitate improved diagnostic tools.
    • The COVID-19 pandemic highlighted the need for efficient medical systems and advanced lung disease diagnostics.
    • Current artificial intelligence models struggle to capture complex time-frequency correlations in lung sound signals.

    Purpose of the Study:

    • To develop an advanced artificial intelligence model for accurate lung sound recognition and disease diagnosis.
    • To address limitations in existing models regarding the capture of multi-scale and time-frequency features.
    • To enhance the efficiency and accuracy of lung disease diagnosis, thereby supporting medical systems.

    Main Methods:

    • Proposed a novel lung sound recognition model incorporating a multi-resolution interleaved net and time-frequency feature enhancement.
    • Utilized a heterogeneous dual-branch time-frequency feature extractor (TFFE) and a branch attention-based feature enhancement module (FEBA).
    • Employed a fusion semantic classifier (FSC) based on semantic mapping for final diagnosis.

    Main Results:

    • The proposed model achieved a high accuracy of 91.56% on a combined dataset.
    • Demonstrated a significant improvement of over 2.13% compared to existing lung sound recognition models.
    • Successfully captured intricate time-frequency correlations and multi-scale features in lung sound data.

    Conclusions:

    • The developed AI model offers a promising approach for accurate and efficient lung disease diagnosis using lung sound analysis.
    • The novel architecture effectively integrates time-frequency information, outperforming previous methods.
    • This technology has the potential to alleviate the strain on healthcare systems and improve patient outcomes for lung conditions.