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 Experiment Video

Updated: Apr 22, 2026

Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in Rats
06:17

Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in Rats

Published on: April 3, 2026

80

Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in

Penghao Liu1, Fengyu Zhang2, Zhuofan Xu1

  • 1Department of Neurosurgery, Xuanwu Hospital, Capital Medical University; Lab of Spinal Cord Injury and Functional Reconstruction, China International Neuroscience Institute (CHNA-INI).

Journal of Visualized Experiments : Jove
|April 20, 2026
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Posttreatment ⁶⁸Ga-FAP-2286 PET/CT Parameters for Response and Survival Assessment After ¹⁷⁷Lu-FAP-2286 Radioligand Therapy in Advanced Solid Tumors.

Clinical nuclear medicine·2026
Same author

Synthetic CT-enabled weekly adaptive radiotherapy for nasopharyngeal carcinoma: Optimizing plan adaptation triggers through volumetric-dosimetric monitoring.

Journal of applied clinical medical physics·2026
Same author

Lineage tracing of soma-to-primordial germ cell-like conversion in human tumor cell line.

iScience·2026
Same author

A novel multi-criteria doctor ranking method considering patient risk attitudes and compensatory relationships.

Health care management science·2026
Same author

Rapidly evolved PD-1 for enhance receptor and checkpoint inhibitor in immunotherapy.

Molecular therapy. Oncology·2026
Same author

Mechanism of liquiritin from Codonopsis pilosula-Glycyrrhiza uralensis extract in alleviating piglet weaning stress via binding to alpha-1-microglobulin/bikunin precursor by machine learning and molecular dynamics simulation.

International journal of biological macromolecules·2026
Same journal

Reliability of A Vibration-Based Elastography Protocol For Assessing Achilles Tendon Stiffness Across Multiple Joint Angles In Elite Athletes.

Journal of visualized experiments : JoVE·2026
Same journal

Associations of Inflammatory and Coagulation Biomarkers with Kidney Injury Across Chronic and Acute Clinical Settings.

Journal of visualized experiments : JoVE·2026
Same journal

Intelligent Recommender Systems for Chinese Super League Fan Consumption Behavior Prediction.

Journal of visualized experiments : JoVE·2026
Same journal

A Battery of Quantitative Binocular Vision Tests for Adults: Testing Protocols.

Journal of visualized experiments : JoVE·2026
Same journal

Efficacy Analysis of Paiteling in Treating Persistent High-Risk Human Papillomavirus after Cervical Cancer Surgery.

Journal of visualized experiments : JoVE·2026
Same journal

Clinical Efficacy of Tissue-Bone Homeostasis Manipulation on Soft Tissue Balance and Function in Knee Osteoarthritis.

Journal of visualized experiments : JoVE·2026
See all related articles
This summary is machine-generated.

This study introduces a markerless treadmill system for objective rat gait analysis, using deep learning to precisely measure hindlimb movement and detect differences in spinal cord injury models.

Area of Science:

  • Neuroscience
  • Kinesiology
  • Biomechanical Engineering

Background:

  • Conventional rat gait analysis relies on indirect footprint imaging, limiting multi-joint kinematic assessment.
  • Objective and precise gait evaluation is crucial for understanding neuromuscular behavior in research.

Purpose of the Study:

  • To develop a markerless, treadmill-based gait analysis system for rodents.
  • To enable real-time, multidimensional kinematic quantification of hindlimb movement.
  • To provide an objective tool for assessing gait alterations in disease models.

Main Methods:

  • Integration of custom deep learning algorithms with a programmable weight-support treadmill.
  • Real-time tracking of multiple lower-limb joints and kinematic parameters.

More Related Videos

3D Kinematic Gait Analysis for Preclinical Studies in Rodents
10:19

3D Kinematic Gait Analysis for Preclinical Studies in Rodents

Published on: August 3, 2019

11.5K
Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories
07:52

Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories

Published on: July 10, 2019

13.7K

Related Experiment Videos

Last Updated: Apr 22, 2026

Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in Rats
06:17

Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in Rats

Published on: April 3, 2026

80
3D Kinematic Gait Analysis for Preclinical Studies in Rodents
10:19

3D Kinematic Gait Analysis for Preclinical Studies in Rodents

Published on: August 3, 2019

11.5K
Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories
07:52

Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories

Published on: July 10, 2019

13.7K
  • Automated extraction of gait cycle parameters, joint trajectories, and force distribution under various conditions (speed, incline, weight support).

    • Main Results:

    • The system accurately quantifies gait parameters, including joint range of motion, trajectory continuity, and movement smoothness.
    • Demonstrated sensitivity in detecting multidimensional gait differences in spinal cord injury (SCI) models.
    • Validated capabilities for disease discrimination and grading compared to traditional methods.

    Conclusions:

    • The developed system offers an objective, high-throughput platform for rodent gait analysis, overcoming limitations of traditional methods.
    • Applicable to diverse research areas including nerve injury, neurodegenerative diseases, and musculoskeletal disorders.
    • Enables synchronous gait and neural signal analysis for understanding central-peripheral control mechanisms.