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Related Concept Videos

Heart Sounds01:15

Heart Sounds

2.3K
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.
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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:
256
Physical Assessment of the Respiratory Tract IV: Auscultation01:28

Physical Assessment of the Respiratory Tract IV: Auscultation

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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.
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Assessment of apical pulse01:17

Assessment of apical pulse

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Assessing the Apical Pulse
Assessing the apical pulse is a critical nursing procedure, particularly indicated for:
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Korotkoff Sounds01:12

Korotkoff Sounds

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Korotkoff sounds are the specific sounds heard while measuring blood pressure using a sphygmomanometer, typically with a stethoscope or a Doppler device. They are named after Russian physician Nikolai Korotkov, who first described them in 1905. These sounds correspond to turbulent blood flow in the artery as the blood pressure cuff is gradually released after inflation.
During blood pressure assessment, inflating the cuff 30 millimeters of mercury above the patient's systolic blood pressure...
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Asthma Detection Research Based on Voice Signal Processing and Machine Learning
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Development of an Electronic Stethoscope and a Classification Algorithm for Cardiopulmonary Sounds.

Yu-Chi Wu1, Chin-Chuan Han2, Chao-Shu Chang3

  • 1Department of Electrical Engineering, National United University, Miaoli City 36003, Taiwan.

Sensors (Basel, Switzerland)
|June 10, 2022
PubMed
Summary
This summary is machine-generated.

An AI-powered electronic stethoscope was developed to improve cardiopulmonary sound analysis. This novel device enhances auscultation accuracy and enables objective recording of heart and lung sounds for better diagnosis.

Keywords:
Mel-frequency cepstral coefficientscardiopulmonary sound classificationelectronic stethoscopeensemble learningprincipal component analysis

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Area of Science:

  • Biomedical Engineering
  • Artificial Intelligence in Medicine
  • Medical Diagnostics

Background:

  • Conventional stethoscopes have limitations in auscultation accuracy due to subjective interpretation and inability to record sounds.
  • Variability in physician training and age-related hearing decline can impact diagnostic consistency.
  • Objective analysis of cardiopulmonary sounds is crucial for accurate diagnosis and treatment.

Purpose of the Study:

  • To develop an electronic stethoscope integrated with an AI-based classifier for objective cardiopulmonary sound analysis.
  • To overcome the limitations of traditional stethoscopes in sound recording and interpretation.
  • To improve the accuracy and consistency of diagnosing heart and lung conditions.

Main Methods:

  • Development of an electronic stethoscope with an embedded condenser microphone and optimized noise reduction circuits.
  • Application of Fast Fourier Transform (FFT) for analyzing microphone placement and noise reduction strategies.
  • Implementation of AI for classifying cardiopulmonary sounds using Mel-frequency cepstral coefficients (MFCC) and ensemble learning on segmented sound frames.

Main Results:

  • The microphone placement surrounded by cork demonstrated superior noise reduction.
  • Distinct AI classifiers were developed for heart and lung sounds, achieving high performance metrics.
  • Optimal performance for heart sound classification included 86.9% accuracy, 81.9% sensitivity, and 91.8% specificity.
  • Lung sound classification achieved 73.3% accuracy, 66.7% sensitivity, and 80% specificity.

Conclusions:

  • The developed electronic stethoscope with AI classification offers a significant advancement over conventional methods.
  • The system provides objective and reliable analysis of cardiopulmonary sounds, aiding in clinical decision-making.
  • This technology has the potential to enhance diagnostic accuracy for various heart and lung pathologies.