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

Classification of Signals01:30

Classification of Signals

1.0K
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
1.0K
Uterine Tubes01:16

Uterine Tubes

1.2K
The uterine or fallopian tubes function as the conduit through which oocytes travel from the ovaries to the uterus. Each fallopian tube measures approximately 10 to 13 cm long and is anatomically divided into the infundibulum, ampulla, isthmus, and interstitial part (or intramural segment). The infundibulum is characterized by its funnel shape and features extensions called fimbriae which reach towards the peritoneal cavity. These fimbriae play a critical role during ovulation as they extend...
1.2K
Smooth Muscle Contraction01:25

Smooth Muscle Contraction

5.1K
Smooth muscle contraction is a complex process vital for various bodily functions, from maintaining blood vessel tension to facilitating the movement of food through the digestive tract. Unlike striated muscles, smooth muscle contraction begins more slowly and lasts longer.
The onset of contraction is triggered by an increase in calcium ions within the sarcoplasm, similar to the process in striated muscle. However, smooth muscles have a relatively smaller reservoir of the sarcoplasmic...
5.1K

You might also read

Related Articles

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

Sort by
Same author

State-of-the-Art Review: Congenital Syphilis in the Modern Era: Current Strategies and Future Directions.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America·2026
Same author

Intravenous immunoglobulin (IVIG) therapy in pregnancies complicated by acute Parvovirus B19 infection in the second trimester: a case series.

Case reports in perinatal medicine·2025
Same author

Acute glycogenic hepatopathy in pregnancy: a case report and literature review.

Case reports in perinatal medicine·2025
Same author

Antepartum multidisciplinary approach improves postpartum pain scores in patients with opioid use disorder.

Journal of perinatal medicine·2025
Same author

Using the PROMOTE Screener to Identify Psychosocial Risk Factors for Prenatal Substance Use.

Journal of addiction medicine·2025
Same author

Vaginal matrix metalloproteinase-9 (MMP-9) as a potential early predictor of preterm birth.

Journal of perinatal medicine·2024

Related Experiment Video

Updated: Oct 15, 2025

Author Spotlight: Advancing Labor Management Through Electromyometrial Imaging for Understanding Uterine Contractions
08:07

Author Spotlight: Advancing Labor Management Through Electromyometrial Imaging for Understanding Uterine Contractions

Published on: May 26, 2023

1.5K

IDENTIFICATION OF UTERINE CONTRACTIONS BY AN ENSEMBLE OF GAUSSIAN PROCESSES.

Liu Yang1, Cassandra Heiselman2, J Gerald Quirk2

  • 1Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY 11794, USA.

Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference)
|October 29, 2021
PubMed
Summary

This study introduces a machine learning approach for identifying uterine contractions, crucial for assessing fetal wellbeing using noisy signals. The novel method shows promising performance in simulations and real-world data.

Keywords:
Gaussian process latent variable modelensemble learninguterine contraction

More Related Videos

Ex Vivo Method for Assessing the Mouse Reproductive Tract Spontaneous Motility and a MATLAB-based Uterus Motion Tracking Algorithm for Data Analysis
06:22

Ex Vivo Method for Assessing the Mouse Reproductive Tract Spontaneous Motility and a MATLAB-based Uterus Motion Tracking Algorithm for Data Analysis

Published on: September 1, 2019

9.2K
Contractility Measurements of Human Uterine Smooth Muscle to Aid Drug Development
07:56

Contractility Measurements of Human Uterine Smooth Muscle to Aid Drug Development

Published on: January 26, 2018

16.8K

Related Experiment Videos

Last Updated: Oct 15, 2025

Author Spotlight: Advancing Labor Management Through Electromyometrial Imaging for Understanding Uterine Contractions
08:07

Author Spotlight: Advancing Labor Management Through Electromyometrial Imaging for Understanding Uterine Contractions

Published on: May 26, 2023

1.5K
Ex Vivo Method for Assessing the Mouse Reproductive Tract Spontaneous Motility and a MATLAB-based Uterus Motion Tracking Algorithm for Data Analysis
06:22

Ex Vivo Method for Assessing the Mouse Reproductive Tract Spontaneous Motility and a MATLAB-based Uterus Motion Tracking Algorithm for Data Analysis

Published on: September 1, 2019

9.2K
Contractility Measurements of Human Uterine Smooth Muscle to Aid Drug Development
07:56

Contractility Measurements of Human Uterine Smooth Muscle to Aid Drug Development

Published on: January 26, 2018

16.8K

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Machine Learning

Background:

  • Accurate identification of uterine contractions is vital for fetal wellbeing assessment.
  • Clinical data, including fetal heart rates, requires robust signal processing for effective analysis.
  • Noisy uterine activity signals pose a challenge to current identification methods.

Purpose of the Study:

  • To develop and evaluate a machine learning-based method for identifying uterine contractions from noisy signals.
  • To improve the accuracy of uterine contraction detection for enhanced fetal monitoring.
  • To address the imbalanced classification problem inherent in uterine activity signal analysis.

Main Methods:

  • A four-step method for uterine contraction identification was proposed.
  • An ensemble Gaussian process classifier was employed to handle imbalanced data.
  • A Gaussian process latent variable model served as the decision-maker within the classification framework.

Main Results:

  • The proposed method demonstrated promising performance in identifying uterine contractions.
  • Simulations and real-world data analysis confirmed the effectiveness of the approach.
  • The method showed superior performance compared to existing techniques for noisy signal processing.

Conclusions:

  • The developed machine learning method offers a robust solution for uterine contraction identification.
  • This approach enhances the potential for integrating uterine activity data with other clinical parameters for fetal wellbeing assessment.
  • The findings support the advancement of intelligent systems for obstetric monitoring.