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

Hypoglycemia01:26

Hypoglycemia

Hypoglycemia is a blood glucose level below 70 mg/dL. It commonly occurs in individuals using insulin or insulin-secreting drugs, but may also arise in non-diabetic conditions. People with type 1 diabetes are at the highest risk because they depend on exogenous insulin. People with type 2 diabetes are also at risk, especially when treated with insulin or medications such as sulfonylureas, which increase insulin release regardless of blood glucose levels. It develops when insulin levels exceed...
Hyperglycemia01:29

Hyperglycemia

Hyperglycemia is an abnormally high blood glucose level. It is diagnosed by fasting glucose ≥126 mg/dL, 2-hour oral glucose tolerance test (or OGTT) ≥200 mg/dL, random glucose ≥200 mg/dL with symptoms, or HbA1c ≥6.5%. However, HbA1c results may be unreliable in certain conditions, such as anemia or hemoglobinopathies, and the diagnosis should be confirmed unless classic symptoms are present. Postprandial hyperglycemia is typically considered significant when glucose levels exceed 180 mg/dL two...
Hypoglycemia and Glucagon01:15

Hypoglycemia and Glucagon

Without prolonged fasting, healthy individuals maintain blood glucose levels above 3.5 mM due to a well-adapted neuroendocrine counterregulatory system that effectively prevents acute hypoglycemia, a potentially life-threatening condition. The primary clinical scenarios for hypoglycemia encompass diabetes treatment, inappropriate production of endogenous insulin or insulin-like substances by tumors, and the use of glucose-lowering agents in non-diabetic individuals. Notably, hypoglycemia in the...
Dysrhythmias V: Evaluating Dysrhythmias01:30

Dysrhythmias V: Evaluating Dysrhythmias

Dysrhythmias, also known as arrhythmias, are disturbances in the heart's rhythm that range from benign to life-threatening. A thorough evaluation is crucial for appropriate management and involves a comprehensive medical history, physical examination, and various diagnostic tests.Medical HistorySymptoms: Collect detailed information on palpitations, dizziness, syncope, chest pain, and fatigue. Note their onset, frequency, and triggers.Previous Cardiac Issues: Document any history of heart...
Dysrhythmias III: Characteristics of Dysrhythmias01:29

Dysrhythmias III: Characteristics of Dysrhythmias

Dysrhythmias, also known as arrhythmias, are irregular heart rhythms that result from abnormal electrical activity in the heart, affecting its ability to circulate blood efficiently. Tachyarrhythmias, a subset of dysrhythmias, are characterized by abnormally fast heart rates exceeding 100 beats per minute. Here are some types of tachyarrhythmias with their distinct ECG features:Sinus Tachycardia:Sinus tachycardia presents a regular heart rhythm with an increased rate of 101-180 beats per minute.
Dysrhythmias I: Introduction01:15

Dysrhythmias I: Introduction

Dysrhythmias refers to abnormalities in the heart's rhythm. They result from disruptions in the heart's electrical conduction system, which includes the sinoatrial(SA)node, atrioventricular(AV) node, the bundle of His, bundle branches, and Purkinje fibers.Definition and PathophysiologyDysrhythmias result from disorders of impulse formation, impulse conduction, or both. The heart contains specialized cells in the sinoatrial node, atrioventricular node, and the bundle of His and Purkinje fibers...

You might also read

Related Articles

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

Sort by
Same author

Clinical trial and real-world evidence of circulating tumor DNA monitoring to predict recurrence in patients with resected colorectal cancer.

ESMO real world data and digital oncology·2026
Same author

Correlation of Doppler indices and umbilical coiling with birthweight and small gestational age prediction in term pregnancies.

Journal of neonatal-perinatal medicine·2026
Same author

Integrated treatment-decision algorithms for childhood TB: modelling diagnostic performance and costs.

IJTLD open·2026
Same author

First report of <i>Pratylenchus parazeae</i> (Nematoda: Pratylenchidae) associated with rice in Vietnam.

Helminthologia·2025
Same author

Development of a questionnaire to screen for chronic obstructive respiratory diseases in low- and middle-income countries.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease·2025
Same author

Validation of a questionnaire to screen chronic obstructive respiratory diseases.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease·2025
Same journal

Analysis of End-Tidal CO2 Variability During Plateau Waves Episodes: An Information Theoretic Approach<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

AI and Tomosynthesis for Breast Cancer Molecular Subtyping: A step toward precision medicine<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Towards Sustainable Protein Recovery from Biological Waste: Assessing Polyethersulfone-based Microfiltration.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Analysis of the cardiovascular response to standardized polymicrobial peritonitis experimental model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Automated Wrist Ultrasound Image Bone Enhancement and Segmentation Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
See all related articles

Related Experiment Video

Updated: May 25, 2026

A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
18:11

A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

Published on: December 28, 2012

Ventricular repolarization variability for hypoglycemia detection.

Steve Ling1, H T Nguyen

  • 1Centre for Health Technologies, Faculty of Engineering and Information Technology, University of Technology, Sydney, Broadway, NSW 2007, Australia. Steve.Ling@uts.edu.au

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|January 19, 2012
PubMed
Summary
This summary is machine-generated.

Hypoglycemia detection in Type 1 diabetes is improved using ventricular repolarization variabilities. A swarm-based support vector machine (SVM) algorithm shows promise for better glycemic management.

More Related Videos

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
06:07

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Published on: May 23, 2021

Homogeneous Time-resolved F&#246;rster Resonance Energy Transfer-based Assay for Detection of Insulin Secretion
07:30

Homogeneous Time-resolved Förster Resonance Energy Transfer-based Assay for Detection of Insulin Secretion

Published on: May 10, 2018

Related Experiment Videos

Last Updated: May 25, 2026

A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
18:11

A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

Published on: December 28, 2012

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
06:07

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Published on: May 23, 2021

Homogeneous Time-resolved F&#246;rster Resonance Energy Transfer-based Assay for Detection of Insulin Secretion
07:30

Homogeneous Time-resolved Förster Resonance Energy Transfer-based Assay for Detection of Insulin Secretion

Published on: May 10, 2018

Area of Science:

  • Biomedical Engineering
  • Cardiology
  • Diabetology

Background:

  • Hypoglycemia is a critical complication of Type 1 diabetes, hindering effective glycemic control.
  • Accurate and timely detection of hypoglycemia is essential for patient safety and management.
  • Ventricular repolarization provides potential physiological markers for metabolic disturbances.

Purpose of the Study:

  • To introduce ventricular repolarization variabilities as novel indicators for hypoglycemia detection.
  • To develop and evaluate a swarm-based support vector machine (SVM) algorithm for hypoglycemia identification using these variabilities.

Main Methods:

  • Analysis of ventricular repolarization variabilities from physiological signals.
  • Development of a swarm-based support vector machine (SVM) model incorporating repolarization variability features.
  • Performance evaluation using sensitivity and specificity metrics.

Main Results:

  • Ventricular repolarization variabilities were identified as relevant features for hypoglycemia detection.
  • The developed swarm-based SVM algorithm achieved a sensitivity of 82.14% and a specificity of 60.19% in detecting hypoglycemia.
  • The combination of repolarization variabilities improved detection performance.

Conclusions:

  • Ventricular repolarization variabilities offer a promising non-invasive approach for hypoglycemia detection in Type 1 diabetes.
  • Swarm-based SVM algorithms can effectively utilize these variabilities for improved diagnostic accuracy.
  • Further research can refine this method for clinical application in diabetes management.