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

Hypoglycemia and Glucagon01:15

Hypoglycemia and Glucagon

266
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...
266
Glucose Homeostasis: Regulation of Blood Glucose01:02

Glucose Homeostasis: Regulation of Blood Glucose

1.6K
Carbohydrates consumed through foods are converted into glucose, a crucial energy source for the body. In the prandial state, high blood glucose levels stimulate the secretion of insulin from the pancreas. Insulin inhibits hepatic glucose production and stimulates glucose uptake and metabolism by muscle and adipose tissue. The excess glucose is converted into glycogen and stored in the liver and muscles.
During fasting, when blood glucose levels are low, the pancreas secretes glucagon. it...
1.6K
Hormones Regulating Blood Glucose01:16

Hormones Regulating Blood Glucose

3.4K
Insulin is released by beta cells of the pancreas when blood glucose levels are high. It facilitates glucose absorption and utilization in insulin-dependent cells with insulin receptors on their plasma membranes. Insulin promotes glucose uptake by increasing the number of glucose transport proteins in the cell membrane, allowing glucose to enter the cell. As a result, glucose utilization and ATP production are enhanced.
In addition to accelerating glucose uptake and utilization, insulin has...
3.4K
Metabolic States of the Body: The Absorptive State01:25

Metabolic States of the Body: The Absorptive State

694
During the absorptive state, which lasts approximately four hours after a meal, the body absorbs nutrients from the gastrointestinal tract. The carbohydrates, proteins, and lipids we consume are broken down into monosaccharides, amino acids, and free fatty acids for absorption. While carbohydrates and proteins are absorbed as-is, lipids are absorbed in their broken-down forms and then re-esterified into triglycerides within enterocytes before being packaged into chylomicrons. These absorbed...
694
Diabetes Mellitus: Type 2 and Gestational01:22

Diabetes Mellitus: Type 2 and Gestational

2.4K
Type 2 diabetes, characterized by insulin resistance, arises when the insulin receptors on cells lose responsiveness to insulin, diminishing the cell's capacity to take up glucose, resulting in elevated blood glucose levels. To receive a diagnosis of Type 2 diabetes, a series of blood glucose tests are necessary to assess whether the blood glucose falls within normal parameters. If the result is out of the normal range, a patient may be diagnosed as prediabetic or diabetic, depending on the...
2.4K

You might also read

Related Articles

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

Sort by
Same author

Gut-brain health effects of PREbiotics in older adults with suspected COgnitive DEcline: design of the PRECODE randomised placebo-controlled trial.

Frontiers in nutrition·2026
Same author

Mapping Digital Nudges and Recommender Systems for Obesity Prevention: Scoping Review.

Interactive journal of medical research·2026
Same author

Validation of the advanced alert monitor in a Dutch hospital using local optimization and refinement of the outcome definition.

International journal of medical informatics·2025
Same author

GameBus on FHIR.

Studies in health technology and informatics·2024
Same author

Predictive modeling of perioperative patient deterioration: combining unanticipated ICU admissions and mortality for improved risk prediction.

Perioperative medicine (London, England)·2024
Same author

Ethnic variations in metabolic syndrome components and their associations with the gut microbiota: the HELIUS study.

Genome medicine·2024
Same journal

Risk prediction of sepsis-associated acute kidney injury: development, validation of a machine learning model with multicenter data.

BMC medical informatics and decision making·2026
Same journal

Trajectory analysis of sleep disorders and anxiety-depression in female breast cancer patients undergoing chemotherapy: based on group-based Multi-Trajectory Model and machine learning.

BMC medical informatics and decision making·2026
Same journal

Multitask learning of longitudinal circulating biomarkers and clinical outcomes: identification of optimal machine-learning and deep-learning models.

BMC medical informatics and decision making·2026
Same journal

Comparative machine learning approaches to prognosticate clinical outcomes in oral and maxillofacial space infections: a retrospective analysis.

BMC medical informatics and decision making·2026
Same journal

Development and validation of machine learning models for early diagnosis of hemophagocytic lymphohistiocytosis in pediatric Epstein-Barr virus infection.

BMC medical informatics and decision making·2026
Same journal

Clinical subphenotypes in septic patients with new-onset atrial fibrillation: validation and parsimonious classifier model development.

BMC medical informatics and decision making·2026
See all related articles

Related Experiment Video

Updated: Jul 9, 2025

A Method for Manipulating Blood Glucose and Measuring Resulting Changes in Cognitive Accessibility of Target Stimuli
08:01

A Method for Manipulating Blood Glucose and Measuring Resulting Changes in Cognitive Accessibility of Target Stimuli

Published on: August 12, 2016

9.0K

Data-driven meal events detection using blood glucose response patterns.

Danilo F de Carvalho1, Uzay Kaymak2, Pieter Van Gorp3

  • 1Jheronimus Academy of Data Science, Eindhoven University of Technology, 's-Hertogenbosch, The Netherlands. d.ferreira.de.carvalho@tue.nl.

BMC Medical Informatics and Decision Making
|December 9, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a personalized, data-driven method for automatic meal detection in diabetes management. The approach accurately identifies individual meal responses, even with external factors, improving artificial pancreas systems.

Keywords:
Continuous glucose monitoring dataDistance profileMeal detectionPattern identificationReal diabetes data

More Related Videos

Author Spotlight: Streamlining Rice Breeding with CRISPR/Cas for Obtaining Optimal Phenotypic and Agronomic Traits
09:43

Author Spotlight: Streamlining Rice Breeding with CRISPR/Cas for Obtaining Optimal Phenotypic and Agronomic Traits

Published on: January 3, 2025

2.4K
Simple Continuous Glucose Monitoring in Freely Moving Mice
03:25

Simple Continuous Glucose Monitoring in Freely Moving Mice

Published on: February 24, 2023

5.5K

Related Experiment Videos

Last Updated: Jul 9, 2025

A Method for Manipulating Blood Glucose and Measuring Resulting Changes in Cognitive Accessibility of Target Stimuli
08:01

A Method for Manipulating Blood Glucose and Measuring Resulting Changes in Cognitive Accessibility of Target Stimuli

Published on: August 12, 2016

9.0K
Author Spotlight: Streamlining Rice Breeding with CRISPR/Cas for Obtaining Optimal Phenotypic and Agronomic Traits
09:43

Author Spotlight: Streamlining Rice Breeding with CRISPR/Cas for Obtaining Optimal Phenotypic and Agronomic Traits

Published on: January 3, 2025

2.4K
Simple Continuous Glucose Monitoring in Freely Moving Mice
03:25

Simple Continuous Glucose Monitoring in Freely Moving Mice

Published on: February 24, 2023

5.5K

Area of Science:

  • Biomedical Engineering
  • Data Science
  • Endocrinology

Background:

  • Meal detection is crucial for diabetes management, particularly in artificial pancreas systems.
  • Blood glucose variations are influenced by multiple factors beyond meals, complicating detection.
  • Existing methods focusing on glucose rate of change are insufficient for personalized factor influence.

Purpose of the Study:

  • To develop a data-driven, individualized approach for automatic meal detection.
  • To accurately identify personalized meal responses in blood glucose data.
  • To account for implicit external factors influencing blood glucose levels.

Main Methods:

  • Individualized pattern identification from blood glucose (BG) signal responses.
  • Similarity evaluation between patterns and BG signal subsequences to identify meal candidates.
  • Utilizing binary classifiers with time and signal-related features for MEAL/NON-MEAL classification.
  • Model selection phase to choose the best performing classifier for each individual.

Main Results:

  • The method successfully detects daily meals with a balanced ratio of detections to false alarms.
  • Performance is good across multiple patients, contingent on sufficient reliable training data.
  • Testing results confirm the approach's effectiveness with adequate data.

Conclusions:

  • The data-driven approach personalizes meal detection by learning individual nuances from data.
  • Models trained on data implicitly capture external factor influences.
  • Potential applications include improving data quality and reminding users of meal events.