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Related Concept Videos

Heart Sounds01:15

Heart Sounds

1.8K
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)...
1.8K
Cardiovascular System Abnormal Findings II: Auscultation01:25

Cardiovascular System Abnormal Findings II: Auscultation

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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:
98
Assessment of the Cardiovascular System IV: Auscultation01:25

Assessment of the Cardiovascular System IV: Auscultation

197
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.
197
Disturbances in Heart Rhythm01:28

Disturbances in Heart Rhythm

886
Arrhythmia or dysrhythmia refers to an abnormal heart rhythm caused by a defect in the heart's conduction system. It can cause the heart to beat irregularly, too quickly, or too slowly, leading to symptoms like chest pain, shortness of breath, and fainting. Factors such as stress, caffeine, alcohol, nicotine, cocaine, certain drugs, congenital defects, diseases, and electrolyte abnormalities can trigger arrhythmias.
Arrhythmias are categorized by their speed, rhythm, and origin. A slow...
886
Pulse rhythm01:30

Pulse rhythm

754
Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...
754

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Related Experiment Video

Updated: May 30, 2025

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
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Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

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Unsupervised segmentation of heart sounds from abrupt changes detection.

Eric Tatulli1, Remi Souriau1, Julie Fontecave-Jallon1

  • 1Univ. Grenoble Alpes, CNRS, CHU Grenoble Alpes, Grenoble INP, TIMC-IMAG, La Tronche, France.

Computers in Biology and Medicine
|January 26, 2025
PubMed
Summary

This study introduces an unsupervised method to segment heart sounds and silences from cardiograms by detecting abrupt signal changes. The algorithm reliably identifies heart states, aiding in cardiovascular disease diagnosis.

Keywords:
Change points detectionHeart soundsUnsupervised segmentation

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Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Cardiology

Background:

  • Early diagnosis of cardiovascular diseases relies on heart auscultation.
  • Automated segmentation of cardiograms into heart states aids physician analysis.
  • Unsupervised segmentation of heart sounds and silences is crucial for effective interpretation.

Purpose of the Study:

  • To propose an unsupervised method for segmenting heart sounds and silences in cardiograms.
  • To detect abrupt signal changes for identifying the beginning and end of heart sounds.
  • To improve the physiological interpretation of heart sound recordings.

Main Methods:

  • Localizing abrupt signal changes corresponding to heart sound boundaries.
  • Calculating signal power within intervals defined by change points to identify sounds and silences.
  • Adjusting algorithm parameters based solely on estimated heart rate.

Main Results:

  • The method was evaluated on three independent databases (PhysioNet 2016, CirCor DigiScope, PASCAL).
  • Achieved high mean F1 scores: 91.2%, 94.3%, and 96.3% across databases.
  • Outperformed most competing unsupervised approaches in detection performance.

Conclusions:

  • The proposed algorithm is reliable, robust, and easy to implement.
  • Demonstrates top-ranking detection performance across diverse heart sound databases.
  • Offers a simple and effective alternative for heart sound segmentation.