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Related Concept Videos

Common Respiratory Disorders01:31

Common Respiratory Disorders

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Respiratory disorders, a prevalent health concern globally, are generally divided into two primary categories: upper and lower respiratory tract disorders. The categorization is based on the area of the respiratory system they affect.
Upper respiratory disorders impact the airways above the vocal cords, encompassing areas like the nose, sinuses, and throat. Various conditions fall under this category, including the common cold and allergic rhinitis. These disorders can stem from several causes,...
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Acute Respiratory Failure-II01:21

Acute Respiratory Failure-II

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Type I Respiratory Failure, or hypoxemic respiratory failure, occurs when the partial pressure of oxygen (PaO2) in arterial blood falls below 60 mmHg while breathing room air without a corresponding increase in arterial carbon dioxide levels (PaCO2). This condition highlights a significant impairment in the lungs' capacity to oxygenate the blood.
The underlying physiological abnormalities that contribute to hypoxemic respiratory failure include:
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Respiratory System Abnormal Finding II: Palpation and Auscultation01:31

Respiratory System Abnormal Finding II: Palpation and Auscultation

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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:
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Pneumonia I: Introduction01:30

Pneumonia I: Introduction

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Pneumonia is an acute respiratory infection that targets the lungs, specifically the alveoli. These tiny air sacs, essential for oxygen exchange, become engorged with pus and fluid, severely hindering breathing, decreasing oxygen absorption, and causing significant pain and discomfort during respiration.
Risk Factors
Various factors influence the likelihood of developing pneumonia. Age plays a crucial role, with infants, children under two, and individuals over 65 at increased risk due to their...
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Chronic Obstructive Pulmonary Disease01:22

Chronic Obstructive Pulmonary Disease

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COPD is defined as a heterogeneous lung condition marked by persistent respiratory symptoms such as dyspnea, cough, and sputum production, caused by abnormalities in the airways that cause airflow obstruction.
Smoking is a primary risk factor for COPD, with over 80% of patients having a history of it. Patients typically experience progressive dyspnea or labored breathing, frequent coughing, and recurrent pulmonary infections. Many eventually succumb to respiratory failure, characterized by...
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Acute Respiratory Failure-III01:30

Acute Respiratory Failure-III

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Hypercapnic respiratory failure, also known as Type 2 or ventilatory respiratory failure, is a severe condition characterized by the body's inability to effectively remove carbon dioxide (CO2) from the bloodstream. It leads to an arterial CO2 pressure (PaCO2) exceeding 45 mmHg and a blood pH above 7.35. This situation indicates that the body's ventilatory demand, or the ventilation needed to maintain normal PaCO2 levels, surpasses its supply or the maximum gas flow achievable without...
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Related Experiment Video

Updated: Oct 12, 2025

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
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Covid-19 recognition from cough sounds using lightweight separable-quadratic convolutional network.

Mohammad Soltanian1, Keivan Borna1

  • 1Faculty of Mathematics and Computer Science, Kharazmi University, Tehran, Iran.

Biomedical Signal Processing and Control
|November 22, 2021
PubMed
Summary

This study introduces a new lightweight deep learning model for classifying cough sounds to detect Covid-19. The model achieves state-of-the-art accuracy and is suitable for low-power, hand-held devices for early infection warnings.

Keywords:
Computational complexityConvolutional neural networkKernel separationMFCCQuadratic convolution

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Area of Science:

  • Artificial Intelligence
  • Medical Diagnostics
  • Signal Processing

Background:

  • Covid-19 symptoms affect the respiratory system, potentially altering cough sounds.
  • Existing deep learning models for sound classification are too large for portable early detection devices.
  • Lightweight models are essential for implementing cough recognition on embedded systems for real-time alerts.

Purpose of the Study:

  • To develop and evaluate a novel, lightweight deep learning model for distinguishing Covid-19 cough sounds.
  • To enable early Covid-19 detection using cough analysis on resource-constrained devices.
  • To address the need for efficient and accurate cough classification algorithms for wearable technology.

Main Methods:

  • Investigated a new lightweight deep learning architecture designed for efficiency.
  • Trained and evaluated the model on the publicly available Virufy dataset, which contains Covid-19 and non-Covid-19 cough recordings.
  • Focused on model design from the outset to ensure suitability for embedded systems.

Main Results:

  • The proposed lightweight model achieved state-of-the-art performance on the Virufy dataset.
  • Demonstrated high accuracy in distinguishing between Covid-19 and non-Covid-19 cough sounds.
  • The model's efficiency makes it a strong candidate for deployment on low-power, hand-held devices.

Conclusions:

  • A new lightweight deep learning model offers a viable solution for early Covid-19 detection via cough analysis.
  • The model's performance and low resource requirements are suitable for practical implementation in mobile health applications.
  • This approach facilitates non-invasive, remote screening for Covid-19, reducing the need for clinical visits.