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

Buoyancy and Stability for Submerged and Floating Bodies01:11

Buoyancy and Stability for Submerged and Floating Bodies

2.1K
In fluid mechanics, buoyancy and stability are key concepts for understanding the behavior of submerged and floating bodies. When a stationary body is fully or partially submerged in a fluid, the fluid exerts a force on the body known as the buoyant force. This force acts vertically upward through a point called the center of buoyancy, which is the center of the displaced fluid volume. According to Archimedes' principle, the magnitude of the buoyant force is equal to the weight of the fluid...
2.1K
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

270
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
270
Neural Control of Respiration01:18

Neural Control of Respiration

3.1K
The neural regulation of respiration is a meticulously coordinated process primarily controlled by the respiratory centers located within the brainstem. These centers, composed of specialized neurons, transmit nerve impulses that control the contraction and relaxation of our respiratory muscles.
Respiratory Centers in the Brainstem
Two primary areas comprise the respiratory center: the medullary respiratory center in the medulla oblongata and the pontine respiratory group in the pons. The...
3.1K

You might also read

Related Articles

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

Sort by
Same author

Association between anxious-depression and cognitive function in community-dwelling older adults: a latent class analysis.

Frontiers in public health·2026
Same author

Recent Advances in Blood-brain Barrier (BBB)-Penetrating Nanomaterials for Neurological Disease Imaging, Diagnosis, and Therapy.

Current neuropharmacology·2026
Same author

Identification and functional characterization of an endophytic Bacillus velezensis strain against Foc TR4 via targeting fungal cell wall integrity.

Pesticide biochemistry and physiology·2026
Same author

Transcriptomic and physiological evidence for magnolol antifungal activity against fusarium oxysporum f. sp. cubense tropical race 4.

Pesticide biochemistry and physiology·2026
Same author

Ensemble Modeling Reveals Threats to Pollination Services From Asynchronous Range Shifts Between <i>Camellia oleifera</i> and Its Specialized Wild Bee Pollinators.

Ecology and evolution·2026
Same author

SARS-CoV-2 infects olfactory neurons and basal stem cells and induces axonal degeneration through TRPV1 activation.

iScience·2026

Related Experiment Video

Updated: Sep 26, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

536

Construction of Swimmer's Underwater Posture Training Model Based on Multimodal Neural Network Model.

Wei Wen1, Tingyu Yang2, Yanhao Fu3

  • 1China Swimming College, Beijing Sport University, Beijing, China.

Computational Intelligence and Neuroscience
|April 22, 2022
PubMed
Summary

This study introduces a new system for monitoring swimming using acceleration sensors and multimodal information fusion. The system accurately detects underwater swimming postures, aiding in personalized training plans.

More Related Videos

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.5K
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

2.0K

Related Experiment Videos

Last Updated: Sep 26, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

536
A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.5K
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

2.0K

Area of Science:

  • Human motion recognition
  • Sports science
  • Wearable technology

Background:

  • Swimming monitoring systems are crucial for performance analysis and training.
  • Existing systems face challenges with single-modal data, environmental interference, and accuracy.
  • Multimodal information fusion offers a promising solution to overcome these limitations.

Purpose of the Study:

  • To develop an intelligent swimming monitoring system using multimodal information fusion.
  • To enhance the accuracy and reliability of underwater swimming posture detection.
  • To create a foundation for personalized swimming training plans.

Main Methods:

  • Utilized an underwater posture training model for multimodal information fusion.
  • Developed an evolutionary neural network optimized by a multimodal adaptive genetic algorithm.
  • Integrated the MPU6050 module for motion and attitude data processing.
  • Conducted experiments measuring four types of swimming postures.

Main Results:

  • The system successfully detected basic swimming postures with high accuracy.
  • Multimodal fusion effectively addressed limitations of single-modal approaches.
  • The optimized neural network ensured system effectiveness in complex environments.
  • Experimental data validated the system's performance and met design requirements.

Conclusions:

  • The developed system provides a robust solution for swimming monitoring.
  • Multimodal information fusion is effective for improving human motion recognition in sports.
  • The system lays the groundwork for advanced swimming analytics and personalized training.