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Related Concept Videos

Heart Sounds01:15

Heart Sounds

4.0K
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)...
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Assessment of the Cardiovascular System IV: Auscultation01:25

Assessment of the Cardiovascular System IV: Auscultation

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Cardiac auscultation is a clinical skill used to assess heart function and detect abnormalities. It involves listening to heart sounds at specific anatomical locations through a stethoscope.
Normal Heart Sounds
S1 (First Heart Sound)-
S1 is made by the closure of the mitral and tricuspid valves (atrioventricular valves), marking the beginning of systole.
S2 (Second Heart Sound)-
S2 is made by the closure of the aortic and pulmonic valves (semilunar valves), marking the end of the systole.
2.2K
Dysrhythmias II: Classification of Tachyarrhythmias01:28

Dysrhythmias II: Classification of Tachyarrhythmias

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Tachyarrhythmias are a type of dysrhythmia where the heart rate exceeds 100 beats per minute. Here are some common types of tachyarrhythmias:Sinus TachycardiaSinus tachycardia originates from increased impulses from the sinus node, leading to an elevated heart rate. It is often triggered by stress, fever, or exercise.Patients may experience palpitations, a sensation of a racing heart, dizziness, and chest discomfort.Causes and Risk Factors: Common causes include physical exertion, emotional...
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Cardiovascular System Abnormal Findings II: Auscultation01:25

Cardiovascular System Abnormal Findings II: Auscultation

710
Auscultation, an essential part of a heart examination, is done using a stethoscope. It provides crucial information about heart function and possible heart problems. Due to heart problems, abnormal sounds can be heard during systole or diastole. These sounds include S3 and S4 gallops, opening snaps, systolic clicks, and murmurs.
Abnormal Heart Sounds
Gallops:
710
Heart Failure IV: Classification and Diagnostic Evaluation01:30

Heart Failure IV: Classification and Diagnostic Evaluation

491
Heart failure can be classified in various ways, with the most common classifications based on physical activity limitations, disease progression, severity, and treatment strategies.The Functional Classification of Heart Failure divides patients into four categories based on physical activity limitation due to symptom burden.Class I: Patients in this class have cardiac disease but no physical activity limitations. Ordinary activities like walking, climbing stairs, or routine tasks do not cause...
491
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

1.7K
Introduction
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin...
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Related Experiment Video

Updated: Mar 2, 2026

Echocardiographic Approaches and Protocols for Comprehensive Phenotypic Characterization of Valvular Heart Disease in Mice
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Echocardiographic Approaches and Protocols for Comprehensive Phenotypic Characterization of Valvular Heart Disease in Mice

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Heart sound classification from unsegmented phonocardiograms.

Philip Langley1, Alan Murray

  • 1School of Engineering and Computer Science, University of Hull, Hull, United Kingdom.

Physiological Measurement
|May 11, 2017
PubMed
Summary
This summary is machine-generated.

This study demonstrates accurate heart sound classification using short, unsegmented phonocardiogram (PCG) recordings. Wavelet entropy and spectral amplitude analysis offer a feasible alternative to complex segmentation methods.

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High-frequency High-resolution Echocardiography: First Evidence on Non-invasive Repeated Measure of Myocardial Strain, Contractility, and Mitral Regurgitation in the Ischemia-reperfused Murine Heart
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Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Cardiology

Background:

  • Automated phonocardiogram (PCG) analysis typically requires segmentation of heart sounds.
  • Segmentation is a complex step in automated PCG analysis.
  • Accurate classification of heart sounds is crucial for diagnosing cardiac conditions.

Purpose of the Study:

  • To assess the feasibility of accurate heart sound classification using short, unsegmented PCG recordings.
  • To evaluate the effectiveness of wavelet entropy and spectral amplitude for heart sound classification.
  • To compare classification performance with and without signal segmentation.

Main Methods:

  • Analysis of 5-second PCG segments from the PhysioNet/Computing in Cardiology Challenge database.
  • Calculation of normalized spectral amplitude using Fast Fourier Transform.
  • Determination of wavelet entropy using wavelet analysis.
  • Implementation of threshold-based classifiers and a classification tree.
  • Comparison of results using initial segments (seg 1) and noise-free segments (seg 2).

Main Results:

  • Significant differences in wavelet entropy and spectral amplitude were found between normal and abnormal recordings.
  • Abnormal recordings showed reduced high-frequency wavelet entropy and increased low-frequency spectral amplitude.
  • Classification accuracy using wavelet entropy reached 76%, improving to 80% with noise-free segments.
  • A classification tree combining features achieved 79% accuracy.

Conclusions:

  • Accurate heart sound classification is feasible without signal segmentation.
  • The proposed method offers comparable accuracy to existing algorithms but with reduced complexity.
  • This approach simplifies automated PCG analysis.