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Heart Sounds

Heart Sounds

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)...

Cardiovascular System Abnormal Findings II: Auscultation

Cardiovascular System Abnormal Findings II: Auscultation

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:

Assessment of the Cardiovascular System IV: Auscultation

Assessment of the Cardiovascular System IV: Auscultation

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.

Equipments Used To Measure Blood Pressure

Equipments Used To Measure Blood Pressure

Direct Method
This invasive approach involves cannulating a peripheral artery. During each cardiac contraction, pressure generates mechanical motion within the catheter, transmitted through rigid, fluid-filled tubing to a transducer. This transducer converts mechanical motion into electrical signals displayed as waveforms on a monitor. An automatic flushing system prevents blood backflow. Due to the potential risk of unexpected arterial blood loss, this method is primarily used in intensive...

Pulse rhythm

Pulse rhythm

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...

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Related Experiment Video

Updated: May 24, 2025

Semi-automated Optical Heartbeat Analysis of Small Hearts

Semi-automated Optical Heartbeat Analysis of Small Hearts

Published on: September 16, 2009

Exploring Pre-trained General-purpose Audio Representations for Heart Murmur Detection.

Daisuke Niizumi, Daiki Takeuchi, Yasunori Ohishi

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

Summary

This study shows that general-purpose audio models, like Masked Modeling Duo (M2D), can improve automated heart murmur detection. Transfer learning with these models offers a promising approach for cardiac auscultation, even with limited heart sound data.

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Area of Science:

Cardiology
Biomedical Engineering
Artificial Intelligence

Background:

Automating cardiac auscultation is crucial for reducing reliance on skilled clinicians.
Deep learning for heart sound analysis requires large datasets, which are often limited.
General-purpose audio models offer pre-trained representations beneficial for specialized tasks.

Purpose of the Study:

To investigate the efficacy of general-purpose audio representations for transfer learning in heart murmur detection.
To evaluate the performance of the Masked Modeling Duo (M2D) model in this context.

Main Methods:

Utilized transfer learning with general-purpose audio representations, specifically the Masked Modeling Duo (M2D) model.
Conducted experiments on the CirCor DigiScope heart sound dataset.
Explored ensembling M2D with other models to further enhance performance.

Main Results:

The Masked Modeling Duo (M2D) model achieved a weighted accuracy of 0.832 and an unweighted average recall of 0.713.
Ensembling M2D with other models led to further performance improvements.
Demonstrated the effectiveness of general-purpose audio representations in processing heart sounds.

Conclusions:

General-purpose audio representations, particularly M2D, are effective for transfer learning in automated heart murmur detection.
This approach shows promise for improving cardiac auscultation, especially with limited specialized data.
The findings pave the way for broader applications of AI in cardiovascular diagnostics.