Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Assessment of Ventilation I: Respiratory Rate01:20

Assessment of Ventilation I: Respiratory Rate

2.0K
Assessment of Ventilation
A Ventilation assessment is critical for monitoring a patient's health status. Respiration, one of the most accessible vital signs, provides insights into the function of numerous body systems and can indicate serious health issues, such as brainstem injuries from head trauma.
Critical Guidelines for Assessing Ventilation:
2.0K
Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies01:27

Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies

3.1K
Assessing and diagnosing Chronic Obstructive Pulmonary Disease (COPD) involves a detailed approach that includes a comprehensive review of medical history, physical examination, and a variety of diagnostic tests. This thorough evaluation is essential to ensure an accurate diagnosis and guide effective management strategies.
Medical History
3.1K
Assessment of Ventilation II: Respiratory Depth and Rhythm01:29

Assessment of Ventilation II: Respiratory Depth and Rhythm

2.4K
Respiratory Depth
Respiratory depth measures the volume of air inhaled or exhaled during a breath. It can vary from shallow to deep and typically remains consistent when a person is at rest or asleep. Occasionally, individuals will automatically inhale deeply, known as sighing, which inflates the lungs with more air than normal breathing.
To assess respiratory depth, observe the degree of chest excursion or movement:
2.4K
Respiratory Assessment: Purpose and Indications01:19

Respiratory Assessment: Purpose and Indications

1.7K
Respiratory assessment is a cornerstone of nursing assessments, crucial for the early detection of patient deterioration. This evaluation transcends routine procedures, representing a critical skill nurses must master to ensure optimal patient care.
Objectives and Importance:
The primary goal of respiratory assessment is to evaluate patients at early risk of clinical deterioration. Since respiratory distress often precedes other signs of declining health, breathing patterns and sounds become a...
1.7K
Assessment of Respiration01:23

Assessment of Respiration

1.8K
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...
1.8K
Pulmonary Function Tests01:25

Pulmonary Function Tests

748
Pulmonary Function Tests (PFTs)
Pulmonary Function Tests are crucial diagnostic tools for assessing respiratory function, particularly in patients with chronic respiratory disorders. They comprehensively evaluate lung volumes, ventilatory function, breathing mechanics, diffusion, and gas exchange. These tests help diagnose pulmonary diseases and play a significant role in monitoring disease progression, evaluating disability, and assessing response to therapy.
PFTs involve using a spirometer, a...
748

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Separation of Molecular Magnets via HPLC with EPR Online Monitoring.

Analytical chemistry·2026
Same author

Solution-synthesized stable triaza[4]triangulene triradical with a quartet ground state.

Nature communications·2026
Same author

Conformation-Variable [7]Annulenyl Radicals.

Chemistry (Weinheim an der Bergstrasse, Germany)·2026
Same author

A Stable Triindenobenzotrithiophene Triradical with Equilateral Ferromagnetic Spin Coupling.

Angewandte Chemie (International ed. in English)·2025
Same author

Reassortment risk of clade 2.3.4.4b H5N1 with avian H9N2 and human H3N2 and H1N1 influenza A viruses.

Science bulletin·2025
Same author

CSAD inhibits excessive inflammation during viral infections through the NF-κB signaling pathway.

Journal of virology·2025

Related Experiment Video

Updated: Jan 17, 2026

Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health
05:51

Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health

Published on: February 21, 2025

1.3K

Smartwatch-based ventilatory assessment for COPD screening: A diagnostic accuracy study.

Yibing Chen1, Lu Cao1, Dahui Zhao1

  • 1Department of Pulmonary and Critical Care Medicine, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China.

Digital Health
|September 22, 2025
PubMed
Summary
This summary is machine-generated.

Smart wearables can screen for Chronic Obstructive Pulmonary Disease (COPD) by analyzing cough sounds and physiological data. This technology offers a scalable solution to improve COPD diagnosis rates where spirometry access is limited.

Keywords:
COPDcough sound analysispulmonary function testsmartwatchwearable devices

More Related Videos

Author Spotlight: Integrating Alveolar-Capillary Reserve Measurements in Exercise Adaptation and Therapeutic Strategies
08:44

Author Spotlight: Integrating Alveolar-Capillary Reserve Measurements in Exercise Adaptation and Therapeutic Strategies

Published on: February 2, 2024

1.2K
Investigation into Deep Breathing through Measurement of Ventilatory Parameters and Observation of Breathing Patterns
08:34

Investigation into Deep Breathing through Measurement of Ventilatory Parameters and Observation of Breathing Patterns

Published on: September 16, 2019

12.1K

Related Experiment Videos

Last Updated: Jan 17, 2026

Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health
05:51

Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health

Published on: February 21, 2025

1.3K
Author Spotlight: Integrating Alveolar-Capillary Reserve Measurements in Exercise Adaptation and Therapeutic Strategies
08:44

Author Spotlight: Integrating Alveolar-Capillary Reserve Measurements in Exercise Adaptation and Therapeutic Strategies

Published on: February 2, 2024

1.2K
Investigation into Deep Breathing through Measurement of Ventilatory Parameters and Observation of Breathing Patterns
08:34

Investigation into Deep Breathing through Measurement of Ventilatory Parameters and Observation of Breathing Patterns

Published on: September 16, 2019

12.1K

Area of Science:

  • Pulmonary Medicine
  • Biomedical Engineering
  • Artificial Intelligence in Healthcare

Background:

  • Chronic Obstructive Pulmonary Disease (COPD) remains underdiagnosed in China due to limited access to spirometry.
  • Smart wearables offer a potential solution for scalable COPD screening through cough and physiological monitoring.

Purpose of the Study:

  • To develop and validate a multimodal screening model for COPD using wearable technology.
  • To assess the accuracy of the model in differentiating COPD patients from healthy individuals.

Main Methods:

  • Machine learning algorithms analyzed cough sounds and smartwatch data (heart rate variability, respiratory rate, oxygen saturation).
  • A multimodal model combined cough features and physiological data to predict lung function.
  • Model performance was evaluated against spirometry and physician diagnoses.

Main Results:

  • The model demonstrated significant correlations between predicted and measured lung function parameters (FVC, FEV1, FEV1/FVC).
  • The combined model achieved high accuracy (87.82%), sensitivity (86.96%), and specificity (87.73%) in differentiating COPD from controls.
  • Mean absolute errors for FEV1/FVC, FVC%, and FEV1% prediction were 7.4%, 10.6%, and 17.78% respectively.

Conclusions:

  • A wearable-based algorithm can effectively screen for ventilatory dysfunction and COPD.
  • This technology shows promise for large-scale population screening, potentially reducing the medical burden of COPD.