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

Sleep Apnea01:21

Sleep Apnea

895
Sleep apnea is a condition where breathing stops intermittently during sleep, often leading to significant health issues. Each episode can last from 10 to 20 seconds or more and is frequently accompanied by a brief arousal from sleep. This disturbance, largely unnoticed by the individual, can lead to severe daytime fatigue. Commonly, individuals seek help after being informed by their partners about loud snoring and noticeable breathing pauses during sleep.
The condition is more prevalent among...
895
Hyperpnea and Hyperventilation01:25

Hyperpnea and Hyperventilation

4.0K
Hyperventilation refers to a higher-than-normal rate and depth of breathing, often associated with anxiety attacks. This excessive breathing surpasses the body's need to expel CO2, leading to a condition known as hypocapnia - an unusually low level of carbon dioxide in the blood. Hypocapnia can constrict cerebral blood vessels, reducing blood flow to the brain, which may result in dizziness or fainting. Early signs include tingling and muscle spasms in the hands and face, caused by falling...
4.0K
Special considerations while measuring oxygen saturation01:19

Special considerations while measuring oxygen saturation

1.0K
Assessing respiratory rate concurrently with pulse measurement is fundamental to patient care, providing valuable insights into the patient's respiratory function. The normal breathing rate for an adult usually falls within a normal range of 12 to 20 breaths per minute. Abnormal respiratory rates can signal underlying health conditions or the need for immediate intervention.
Ensuring accuracy in vital sign recordings while prioritizing patient comfort and minimizing anxiety is...
1.0K
Assessment of Ventilation I: Respiratory Rate01:20

Assessment of Ventilation I: Respiratory Rate

2.8K
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:
2.8K
Physical Assessment of the Respiratory Tract II: Inspection01:27

Physical Assessment of the Respiratory Tract II: Inspection

1.4K
Physical assessment of the respiratory tract through inspection is a crucial step in understanding the patient's respiratory health. It provides insights into the functioning of the respiratory system, the musculoskeletal structure, and even the patient's nutritional status. This comprehensive approach involves observing several vital aspects: chest configuration, breathing patterns, respiratory rates, skin color, and use of accessory muscles.
Chest Configuration
The chest configuration...
1.4K
Respiratory Volumes and Capacities I01:26

Respiratory Volumes and Capacities I

2.0K
Assessing the respiratory rate and rhythm for a complete minute is crucial for evaluating the breathing pattern. Even a minor increase in the patient's average respiratory rate, by as little as three to five breaths per minute, is an early and vital indicator of respiratory distress. Patients with a respiratory rate exceeding twenty-four breaths per minute require close monitoring to determine the physiological alterations. This careful observation is essential for prompt recognition and...
2.0K

You might also read

Related Articles

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

Sort by
Same author

Critical habitat size of organisms diffusing with stochastic resetting.

Physical review. E·2025
Same author

Analytical insights from a model of opinion formation based on persuasive argument theory.

Physical review. E·2025
Same author

Random search with resetting in heterogeneous environments.

Physical review. E·2024
Same author

Noisy kinetic-exchange opinion model with aging.

Physical review. E·2024
Same author

Approaching the perfect diode limit through a nonlinear interface.

Physical review. E·2023
Same author

Machine discovery of partial differential equations from spatiotemporal data: A sparse Bayesian learning framework.

Chaos (Woodbury, N.Y.)·2023
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Apr 23, 2026

A Model to Simulate Clinically Relevant Hypoxia in Humans
09:54

A Model to Simulate Clinically Relevant Hypoxia in Humans

Published on: December 22, 2016

8.5K

Sleep apnea-hypopnea quantification by cardiovascular data analysis.

Sabrina Camargo1, Maik Riedl2, Celia Anteneodo3

  • 1Department of Physics, Humboldt-Universität zu Berlin, Berlin, Germany; EMAp, Fundação Getúlio Vargas, Rio de Janeiro, Brazil; Department of Physics, PUC-Rio, Rio de Janeiro, Brazil.

Plos One
|September 16, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method to detect sleep apnea using systolic blood pressure (SBP) time series analysis. The findings show that SBP patterns can accurately identify sleep apnea, offering an alternative to traditional polysomnography.

More Related Videos

Multi-Modal Home Sleep Monitoring in Older Adults
07:40

Multi-Modal Home Sleep Monitoring in Older Adults

Published on: January 26, 2019

7.3K
Quantitative Autonomic Testing
11:40

Quantitative Autonomic Testing

Published on: July 19, 2011

59.2K

Related Experiment Videos

Last Updated: Apr 23, 2026

A Model to Simulate Clinically Relevant Hypoxia in Humans
09:54

A Model to Simulate Clinically Relevant Hypoxia in Humans

Published on: December 22, 2016

8.5K
Multi-Modal Home Sleep Monitoring in Older Adults
07:40

Multi-Modal Home Sleep Monitoring in Older Adults

Published on: January 26, 2019

7.3K
Quantitative Autonomic Testing
11:40

Quantitative Autonomic Testing

Published on: July 19, 2011

59.2K

Area of Science:

  • Cardiology
  • Sleep Medicine
  • Biomedical Engineering

Background:

  • Sleep disorders, particularly sleep apnea, are significant risk factors for cardiovascular diseases.
  • Current detection of sleep apnea necessitates polysomnography, a complex and resource-intensive overnight monitoring process.

Purpose of the Study:

  • To develop a method for detecting sleep apnea using only systolic blood pressure (SBP) time series data.
  • To identify quantifiable metrics from SBP signals that correlate with sleep apnea severity.

Main Methods:

  • Applied a segmentation procedure to nonstationary SBP time series to identify stationary patches.
  • Extracted local signal quantities including mean, variance, and duration (L) from these patches.
  • Analyzed data from 26 diagnosed apneic individuals (hypertensive and normotensive) and a control group.

Main Results:

  • Identified correlations between average duration () and average variance (<σ2>) of SBP patches with the apnea-hypoapnea index (AHI).
  • Discovered an oscillatory pattern in apneic subjects, with amplitude (S*) also correlating with AHI.
  • Achieved at least 79% accuracy in separating apneic individuals using these SBP-derived metrics.

Conclusions:

  • Quantifiable features extracted from SBP time series can serve as alternative criteria for sleep apnea detection.
  • This approach offers a simpler, single-time series-based method for identifying sleep apnea, potentially reducing reliance on polysomnography.