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Respiratory System Abnormal Finding II: Palpation and Auscultation01:31

Respiratory System Abnormal Finding II: Palpation and Auscultation

2.0K
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:
2.0K
Respiratory System Abnormal Finding I: Inspection and Percussion01:30

Respiratory System Abnormal Finding I: Inspection and Percussion

1.2K
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...
1.2K
Physical Assessment of the Respiratory Tract IV: Auscultation01:28

Physical Assessment of the Respiratory Tract IV: Auscultation

3.6K
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.
3.6K
Assessment of Respiration01:23

Assessment of Respiration

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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...
2.4K
Physical Assessment of the Respiratory Tract III: Percussion01:29

Physical Assessment of the Respiratory Tract III: Percussion

4.6K
The respiratory system, fundamental to life, consists of complex structures responsible for gas exchange. The percussion assessment is critical to understanding this system's health and functionality. This non-invasive assessment technique allows healthcare providers to evaluate the density or aeration of the lungs, thereby identifying potential abnormalities.
Percussion in Respiratory Assessment
Percussion evaluates underlying tissue composition with audible and tactile vibrations,...
4.6K
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:
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Related Experiment Video

Updated: Apr 11, 2026

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

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Using K-Nearest Neighbor Classification to Diagnose Abnormal Lung Sounds.

Chin-Hsing Chen1, Wen-Tzeng Huang2, Tan-Hsu Tan3

  • 1Department of Management Information Systems, Central Taiwan University of Science and Technology, Taichung 40601, Taiwan, China. chchen@ctust.edu.tw.

Sensors (Basel, Switzerland)
|June 9, 2015
PubMed
Summary

A new digital stethoscope system analyzes lung sounds using mel-frequency cepstral coefficients (MFCCs) and K-nearest neighbor classification. This technology aids in diagnosing abnormal lung sounds and offers potential for home care monitoring.

Keywords:
K-means algorithmK-nearest neighborMFCClung soundstethoscope

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Area of Science:

  • Biomedical Engineering
  • Medical Acoustics
  • Digital Health

Background:

  • Abnormal lung sounds affect 30% of the global population.
  • Traditional stethoscopes have limitations including environmental noise interference, lack of data recording, and subjective interpretation.
  • These limitations hinder accurate and consistent diagnosis of respiratory conditions.

Purpose of the Study:

  • To develop a digital stethoscope system for improved diagnosis of abnormal lung sounds.
  • To incorporate a respiration detector for real-time monitoring and home care applications.
  • To overcome the limitations of traditional stethoscopes in clinical and remote settings.

Main Methods:

  • Lung sound feature extraction using mel-frequency cepstral coefficients (MFCCs).
  • Feature clustering with the K-means algorithm for computational efficiency.
  • Lung sound classification via the K-nearest neighbor (KNN) method.
  • Development of a respiration detector using bend sensors, amplification circuits, and Bluetooth for real-time respiratory cycle assessment.

Main Results:

  • The digital stethoscope system effectively classifies lung sounds.
  • The integrated respiration detector achieved a low error rate of 6.8% in respiratory cycle measurement.
  • The system provides automatic warnings for potential health issues, indicating suitability for home care.

Conclusions:

  • The developed digital stethoscope offers a promising solution for accurate and objective lung sound analysis.
  • The integrated respiration detector demonstrates high accuracy and potential for remote patient monitoring.
  • This technology can enhance early diagnosis and management of respiratory conditions, particularly in home care settings.