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

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

412
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
412
Neural Regulation of Blood Pressure01:18

Neural Regulation of Blood Pressure

9.4K
The neural regulation of blood pressure involves intricate interactions between the autonomic nervous system (ANS) and cardiovascular system, ensuring adequate perfusion of tissues. This regulation primarily occurs through baroreceptor and chemoreceptor reflexes, involving both short-term and long-term mechanisms.
Baroreceptor Reflex
Baroreceptors, located in the carotid sinuses and aortic arch, detect changes in blood pressure. When blood pressure rises, these stretch-sensitive receptors...
9.4K
Blood Pressure Imbalances and Circulatory Shock01:24

Blood Pressure Imbalances and Circulatory Shock

1.9K
Disorders affecting blood volume, vascular tone, or vascular function can disrupt vascular homeostasis, including conditions like hypertension, hemorrhage, and shock.
Blood Pressure: Hypertension and Hypotension
Normal blood pressure is 120/80 mm Hg. Elevated blood pressure is 120-129/under 80 mm Hg. Hypertension, warranting treatment at 130/80 mm Hg, is often asymptomatic and can lead to severe cardiovascular events, aneurysms, peripheral arterial disease, chronic renal disease, or cardiac...
1.9K
Alterations in Blood Pressure01:30

Alterations in Blood Pressure

2.5K
Alterations in blood pressure, such as hypertension (high blood pressure) and hypotension (low blood pressure), significantly affect human health. Understanding these conditions' classifications, causes, and symptoms is essential for effective management and treatment.
Hypertension (High blood pressure)
Hypertension occurs when blood pressure readings consistently exceed the normal range. It is diagnosed when systolic blood pressure (the top number, indicating pressure while the heart...
2.5K
Hypertension and Regulation of Blood Pressure01:18

Hypertension and Regulation of Blood Pressure

4.8K
Hypertension, the most common cardiovascular disease, is diagnosed through repeated measurements of elevated blood pressure. Its risks, including damage to the kidney, heart, and brain, are directly proportional to blood pressure levels. Starting from 115/75 mm Hg, the risk of cardiovascular disease doubles with each increment of 20/10 mm Hg. The diagnosis relies on blood pressure measurements, not on patient symptoms, as hypertension is often asymptomatic until end-organ damage is imminent or...
4.8K
Chronopharmacokinetics: Circadian Rhythms and Influence on Drug Response01:15

Chronopharmacokinetics: Circadian Rhythms and Influence on Drug Response

480
Circadian rhythms are cyclic changes that are crucial in plasma drug concentrations. Various standard circadian parameters, including core body temperature, heart rate, and other cardiovascular factors, directly impact disease states and the therapeutic response to drug therapy.
The time of drug administration is an important factor to consider, as it can influence the toxic dose of a drug. For example, a study conducted by Prins et al. in 1997 examined the effects of the timing of...
480

You might also read

Related Articles

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

Sort by
Same author

Metal surface-triggered DNAzyme catalysis for efficient DNA cleavage.

Communications chemistry·2026
Same author

The Influence of Y<sub>2</sub>O<sub>3</sub> Dosage on the Performance of Fe60/WC Laser Cladding Coating.

Molecules (Basel, Switzerland)·2025
Same author

Frontal Polymerization-Enabled 3D Printing of Recyclable High-Performance Carbon Fiber Reinforced Polymers.

Advanced materials (Deerfield Beach, Fla.)·2025
Same author

Highly-Oriented Polylactic Acid Fiber Reinforced Polycaprolactone Composite Produced by Infused Fiber Mat Process for 3D Printed Tissue Engineering Technology.

Polymers·2025
Same author

ICE: A Driver Genes Identification Method With Improved Cross-Entropy Measure.

IEEE transactions on computational biology and bioinformatics·2025
Same author

A fluorescent biosensor based on glucose oxidase-DNAzyme/substrate complex synergy for salivary glucose monitoring.

Analytical and bioanalytical chemistry·2025

Related Experiment Video

Updated: Apr 12, 2026

Development of an Algorithm to Perform a Comprehensive Study of Autonomic Dysreflexia in Animals with High Spinal Cord Injury Using a Telemetry Device
06:51

Development of an Algorithm to Perform a Comprehensive Study of Autonomic Dysreflexia in Animals with High Spinal Cord Injury Using a Telemetry Device

Published on: July 29, 2016

8.3K

[Acute hypotensive episodes prediction based on non-linear chaotic analysis].

Dazhi Jiang, Liyu Li, Chenfeng Peng

    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi = Journal of Biomedical Engineering = Shengwu Yixue Gongchengxue Zazhi
    |May 23, 2015
    PubMed
    Summary

    Predicting acute hypotensive episodes (AHE) in intensive care units (ICU) is crucial. Chaos signal analysis of mean arterial pressure revealed curve mutations preceding AHE, offering a basis for early detection.

    More Related Videos

    Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression
    11:26

    Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression

    Published on: December 10, 2014

    12.9K
    Integrated Compensatory Responses in a Human Model of Hemorrhage
    07:57

    Integrated Compensatory Responses in a Human Model of Hemorrhage

    Published on: November 20, 2016

    13.3K

    Related Experiment Videos

    Last Updated: Apr 12, 2026

    Development of an Algorithm to Perform a Comprehensive Study of Autonomic Dysreflexia in Animals with High Spinal Cord Injury Using a Telemetry Device
    06:51

    Development of an Algorithm to Perform a Comprehensive Study of Autonomic Dysreflexia in Animals with High Spinal Cord Injury Using a Telemetry Device

    Published on: July 29, 2016

    8.3K
    Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression
    11:26

    Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression

    Published on: December 10, 2014

    12.9K
    Integrated Compensatory Responses in a Human Model of Hemorrhage
    07:57

    Integrated Compensatory Responses in a Human Model of Hemorrhage

    Published on: November 20, 2016

    13.3K

    Area of Science:

    • Critical Care Medicine
    • Biomedical Engineering
    • Data Science

    Background:

    • Acute hypotensive episodes (AHE) pose a significant challenge in intensive care units (ICU).
    • Predicting AHE is vital for timely clinical intervention and improved patient outcomes.
    • Current predictive methods may lack sufficient sensitivity or specificity.

    Purpose of the Study:

    • To investigate the potential of chaos signal analysis for predicting AHE in ICU patients.
    • To identify early warning signs of AHE using computational methods.
    • To establish a basis for theoretical and clinical advancements in AHE management.

    Main Methods:

    • Utilized patient data from the MIMIC II clinical database.
    • Applied chaos signal analysis techniques to time series of mean arterial pressure.
    • Generated Lyapunov exponent curves to analyze signal dynamics.

    Main Results:

    • Observed distinct curve mutations in the Lyapunov exponent analysis prior to the onset of AHE symptoms.
    • These mutations provide a clear and powerful indicator for AHE determination.
    • The findings suggest a predictable pattern preceding hypotensive events.

    Conclusions:

    • Chaos signal analysis of mean arterial pressure can identify pre-symptomatic indicators of AHE.
    • This method offers a promising computational approach for early AHE detection in ICUs.
    • The study provides a foundation for further research and clinical application in predicting and managing AHE.