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

You might also read

Related Articles

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

Sort by
Same author

Gentle-Sketch: a high-performance and compact invertible sketch for top-K estimation.

Scientific reports·2026
Same author

Computational biomechanics of human knee joint in maximum voluntary isometric extension with focus on the role of joint center positioning.

Scientific reports·2026
Same author

Lumbosacral orthosis can improve postural control in older adults with chronic low back pain.

BMC musculoskeletal disorders·2026
Same author

Biomechanical effects of partial and full L4-L5 disc nucleotomy: a coupled musculoskeletal finite element modeling study.

Journal of orthopaedic surgery and research·2026
Same author

Development and validation of a subject-specific integrated finite element musculoskeletal model of human trunk with ergonomic and clinical applications.

Biomechanics and modeling in mechanobiology·2025
Same author

Effect of a back-support exoskeleton on internal forces and lumbar spine stability during low load lifting task.

Applied ergonomics·2024

Related Experiment Video

Updated: Jul 2, 2025

Biomechanical Changes Related to Low Back Pain: An Innovative Tool for Movement Pattern Assessment and Treatment Evaluation in Rehabilitation
06:28

Biomechanical Changes Related to Low Back Pain: An Innovative Tool for Movement Pattern Assessment and Treatment Evaluation in Rehabilitation

Published on: December 13, 2024

501

Machine learning applications in spine biomechanics.

Farshid Ghezelbash1, Amir Hossein Eskandari2, Xavier Robert-Lachaine3

  • 1Division of Applied Mechanics, Department of Mechanical Engineering, Polytechnique Montréal, Canada.

Journal of Biomechanics
|February 22, 2024
PubMed
Summary

Machine learning and computer vision are transforming spine biomechanics research. This study presents a framework using these technologies for accessible 3D analysis, aiding injury prevention and performance optimization.

More Related Videos

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
09:32

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion

Published on: April 11, 2018

9.7K
A Spine Robotic-Assisted Navigation System for Pedicle Screw Placement
06:24

A Spine Robotic-Assisted Navigation System for Pedicle Screw Placement

Published on: May 11, 2020

8.8K

Related Experiment Videos

Last Updated: Jul 2, 2025

Biomechanical Changes Related to Low Back Pain: An Innovative Tool for Movement Pattern Assessment and Treatment Evaluation in Rehabilitation
06:28

Biomechanical Changes Related to Low Back Pain: An Innovative Tool for Movement Pattern Assessment and Treatment Evaluation in Rehabilitation

Published on: December 13, 2024

501
Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
09:32

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion

Published on: April 11, 2018

9.7K
A Spine Robotic-Assisted Navigation System for Pedicle Screw Placement
06:24

A Spine Robotic-Assisted Navigation System for Pedicle Screw Placement

Published on: May 11, 2020

8.8K

Area of Science:

  • Biomechanics
  • Computer Science
  • Machine Learning

Background:

  • Spine biomechanics research is evolving with new computational technologies.
  • Machine learning (ML) and computer vision (CV) enable 3D body shape, anthropometrics, and kinematics estimation from single images.
  • These advancements offer more accessible and practical tools for biomechanical analysis.

Purpose of the Study:

  • To introduce a framework integrating ML/CV with musculoskeletal modeling for comprehensive spine biomechanics analysis.
  • To evaluate the performance and limitations of these technologies in real-world spine biomechanics applications.
  • To explore applications in workplace safety, injury assessment (e.g., whiplash), and sports performance.

Main Methods:

  • Development of a novel framework combining ML/CV techniques with traditional musculoskeletal modeling.
  • Utilizing single-camera imaging for data acquisition.
  • Validation of the framework across diverse applications including industrial, forensic, and sports settings.

Main Results:

  • Demonstrated potential of ML/CV algorithms for estimating body shape, kinematics, and in-field biomechanical analyses.
  • Identified specific limitations, including prediction accuracy, complex interaction modeling, and external load estimation.
  • Showcased applicability in workplace injury risk assessment, sports performance optimization, and forensic analysis.

Conclusions:

  • The integrated framework shows significant potential for advancing spine biomechanics research and applications.
  • ML/CV technologies offer promising avenues for preventive measures against back injuries in industrial settings.
  • The study highlights opportunities for performance enhancement, injury prevention, and rehabilitation in sports through advanced biomechanical analysis.