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

Physical Assessment of the Respiratory Tract IV: Auscultation01:28

Physical Assessment of the Respiratory Tract IV: Auscultation

255
Auscultation is a crucial component of the physical assessment of the respiratory tract. It offers valuable insights into airflow through the bronchial tree and potential lung obstructions. This process involves careful listening to breath, voice, and adventitious sounds, which can reveal a wealth of information about a patient's respiratory health.
Breath Sounds
Breath sounds are categorized into vesicular, bronchovesicular, and bronchial.
255
Assessment of Respiration01:23

Assessment of Respiration

1.0K
The respiratory system's basic structures and primary functions lay the foundation for nurses' comprehensive respiratory assessments. This assessment includes subjective and objective data to gauge the patient's respiratory health.
Subjective Assessment: Nurses interview the patient to gather information directly during the subjective assessment. It includes questions about the individual's medical history, medications, and symptoms, focusing on past respiratory conditions like...
1.0K
Respiratory System Abnormal Finding II: Palpation and Auscultation01:31

Respiratory System Abnormal Finding II: Palpation and Auscultation

253
In assessing respiratory abnormalities, palpation and auscultation are critical tools for detecting and interpreting various pathophysiological changes. These techniques provide insight into underlying disorders by evaluating tactile sensations and sounds produced by the respiratory system.
Palpation Findings
During a respiratory assessment, palpation can reveal several vital abnormalities:
253
Respiratory System Abnormal Finding I: Inspection and Percussion01:30

Respiratory System Abnormal Finding I: Inspection and Percussion

195
Respiratory system abnormalities are a significant concern in healthcare due to their potential to indicate underlying severe conditions like Chronic Obstructive Pulmonary Disease (COPD), asthma, and pneumonia. These abnormalities can often be detected through physical examination methods like inspection and percussion.
Inspection Findings
During an inspection, several findings may suggest the presence of respiratory distress or disease. Pursed-lip breathing, where exhalation is slowed by...
195
Heart Sounds01:15

Heart Sounds

1.7K
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)...
1.7K
Classification of Signals01:30

Classification of Signals

374
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
374

You might also read

Related Articles

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

Sort by
Same author

Exploring the Real-World Effectiveness of Empagliflozin and Linagliptin Fixed-Dose Combination in Type 2 Diabetes Patients of Bangladesh: A Prospective Multi-Center Observational Study.

Diabetes, metabolic syndrome and obesity : targets and therapy·2025
Same author

NeuroNet-AD: A Multimodal Deep Learning Framework for Multiclass Alzheimer's Disease Diagnosis.

Bioengineering (Basel, Switzerland)·2025
Same author

MicroAIbiome: Decoding Cancer Types from Microbial Profiles Using Explainable Machine Learning.

Microorganisms·2025
Same author

Text-Assisted Vision Model for Medical Image Segmentation.

IEEE journal of biomedical and health informatics·2025
Same author

Photobiomodulation Therapy: Survey and Principal Study Leading to Design Rules for Implants.

IEEE transactions on bio-medical engineering·2025
Same author

Integrated Gene Expression Data-Driven Identification of Molecular Signatures, Prognostic Biomarkers, and Drug Targets for Glioblastoma.

BioMed research international·2024

Related Experiment Video

Updated: May 24, 2025

Flying Insect Detection and Classification with Inexpensive Sensors
05:16

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

25.1K

Adventitious Pulmonary Sound Detection: Leveraging SHAP Explanations and Gradient Boosting Insights.

Shiva Shokouhmand, Md Motiur Rahman, Miad Faezipour

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 5, 2025
    PubMed
    Summary

    This study developed an automated method using XGBoost to diagnose respiratory diseases from lung sound recordings. The system achieved high accuracy, improving early detection of pulmonary conditions.

    More Related Videos

    Author Spotlight: Exploring Breathing Techniques and Digital Solutions for Enhancing Running Performance
    06:26

    Author Spotlight: Exploring Breathing Techniques and Digital Solutions for Enhancing Running Performance

    Published on: September 27, 2024

    356
    Contrast-Enhanced Subharmonic Aided Pressure Estimation SHAPE Using Ultrasound Imaging with a Focus on Identifying Portal Hypertension
    06:20

    Contrast-Enhanced Subharmonic Aided Pressure Estimation SHAPE Using Ultrasound Imaging with a Focus on Identifying Portal Hypertension

    Published on: December 5, 2020

    2.3K

    Related Experiment Videos

    Last Updated: May 24, 2025

    Flying Insect Detection and Classification with Inexpensive Sensors
    05:16

    Flying Insect Detection and Classification with Inexpensive Sensors

    Published on: October 15, 2014

    25.1K
    Author Spotlight: Exploring Breathing Techniques and Digital Solutions for Enhancing Running Performance
    06:26

    Author Spotlight: Exploring Breathing Techniques and Digital Solutions for Enhancing Running Performance

    Published on: September 27, 2024

    356
    Contrast-Enhanced Subharmonic Aided Pressure Estimation SHAPE Using Ultrasound Imaging with a Focus on Identifying Portal Hypertension
    06:20

    Contrast-Enhanced Subharmonic Aided Pressure Estimation SHAPE Using Ultrasound Imaging with a Focus on Identifying Portal Hypertension

    Published on: December 5, 2020

    2.3K

    Area of Science:

    • Medical Informatics
    • Signal Processing
    • Machine Learning

    Background:

    • Pulmonary illnesses are a significant global health concern with high prevalence.
    • Early diagnosis of respiratory diseases is crucial for improving patient outcomes.
    • Automated diagnostic tools can enhance the efficiency and accuracy of clinical assessments.

    Purpose of the Study:

    • To develop an automated, explainable method for diagnosing respiratory diseases based on adventitious lung sounds.
    • To segment stethoscope audio recordings to isolate normal and abnormal respiratory sounds (e.g., wheezing, crackling).
    • To identify key audio features that effectively discriminate between different respiratory conditions.

    Main Methods:

    • Respiratory sound recordings were segmented to isolate normal and adventitious lung sounds.
    • A comprehensive feature set capturing temporal and spectral dynamics was extracted.
    • An Extreme Gradient Boosting (XGBoost) model was trained and validated using a five-fold cross-validation on the ICBHI 2017 dataset.
    • Shapley values were computed to enhance the explainability of the XGBoost model's predictions.

    Main Results:

    • The developed XGBoost model achieved high performance metrics: 94.57% specificity, 77.96% sensitivity, and an ICBHI score of 86.27%.
    • The method outperformed existing state-of-the-art techniques in diagnosing respiratory conditions from lung sounds.
    • Key discriminating features identified include Mel-frequency cepstral coefficients (MFCC), spectral centroid, zero crossing rate, and signal intensity.

    Conclusions:

    • The automated lung sound analysis method provides a reliable and explainable approach for diagnosing respiratory diseases.
    • The findings support the integration of such technologies into smart digital stethoscopes and remote patient monitoring systems.
    • This technology has significant potential for early detection and personalized healthcare in clinical and telemedicine settings.