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

Predicting pain location from resting-state brain fMRI.

bioRxiv : the preprint server for biology·2026
Same author

Large language models for automated and audience-tailored labeling of latent classes.

JAMIA open·2026
Same author

Reachable Workspace as a Clinical Outcome for Upper Extremity Function: A Narrative Review.

Muscle & nerve·2026
Same author

Automated Annotation of Pain Chronicity in Patients With Back Pain by Using Electronic Health Records: Retrospective Study.

JMIR formative research·2026
Same author

Comparing Movement Patterns and Physical Function Between Chronic Low Back Pain Patients With Nociplastic and Nociceptive Pain Categories.

JOR spine·2026
Same author

Empowering Self-Management of Chronic Low Back Pain Among Spanish and Cantonese Speakers in the United States.

Cureus·2025
Same journal

An Ultra-Lightweight Cross-scale Attention Mamba Network for Accurate Skin Lesion Segmentation.

IEEE journal of biomedical and health informatics·2026
Same journal

Explanation-Guided Reconstruction of Missing Clinical Features for Survival Prediction in Pancreatic Cancer.

IEEE journal of biomedical and health informatics·2026
Same journal

stDGCN: A dual-augmentation graph convolutional network for identifying spatial domains with attention mechanism.

IEEE journal of biomedical and health informatics·2026
Same journal

Patient-specific Biomechanical Investigation of Percutaneous Pulmonary Valves: Towards the Integration of Routinely Acquired Clinical Data and Fluid-structure Interaction Simulations.

IEEE journal of biomedical and health informatics·2026
Same journal

Cross-subject fMRI-to-Image with Visual-cortex 2D Representation and Pre-Training.

IEEE journal of biomedical and health informatics·2026
Same journal

PGCASurv: A Prior-Guided Cross-Attention Framework for Dynamic Survival Model with Longitudinal Data.

IEEE journal of biomedical and health informatics·2026
See all related articles

Related Experiment Video

Updated: Dec 23, 2025

Kinematic Analysis Using 3D Motion Capture of Drinking Task in People With and Without Upper-extremity Impairments
08:45

Kinematic Analysis Using 3D Motion Capture of Drinking Task in People With and Without Upper-extremity Impairments

Published on: March 28, 2018

11.1K

Reachable Workspace and Proximal Function Measures for Quantifying Upper Limb Motion.

Robert P Matthew, Sarah Seko, Gregorij Kurillo

    IEEE Journal of Biomedical and Health Informatics
    |April 29, 2020
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new method using rigid body modeling to improve the accuracy of upper limb function assessments with depth cameras. The enhanced reachable workspace (RW) and proximal function (PF) measures show promise for clinical use.

    More Related Videos

    The Impact of Motor Task Conditions on Goal-Directed Arm Reaching Kinematics and Trunk Compensation in Chronic Stroke Survivors
    15:00

    The Impact of Motor Task Conditions on Goal-Directed Arm Reaching Kinematics and Trunk Compensation in Chronic Stroke Survivors

    Published on: May 2, 2021

    3.9K
    Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography
    04:06

    Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography

    Published on: January 12, 2024

    949

    Related Experiment Videos

    Last Updated: Dec 23, 2025

    Kinematic Analysis Using 3D Motion Capture of Drinking Task in People With and Without Upper-extremity Impairments
    08:45

    Kinematic Analysis Using 3D Motion Capture of Drinking Task in People With and Without Upper-extremity Impairments

    Published on: March 28, 2018

    11.1K
    The Impact of Motor Task Conditions on Goal-Directed Arm Reaching Kinematics and Trunk Compensation in Chronic Stroke Survivors
    15:00

    The Impact of Motor Task Conditions on Goal-Directed Arm Reaching Kinematics and Trunk Compensation in Chronic Stroke Survivors

    Published on: May 2, 2021

    3.9K
    Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography
    04:06

    Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography

    Published on: January 12, 2024

    949

    Area of Science:

    • Biomechanics
    • Rehabilitation Engineering
    • Clinical Assessment

    Background:

    • Quantitative assessment of upper limb function lacks precise clinical tools.
    • Conventional biomechanical measures require expensive, complex lab equipment and specialist analysis.
    • Depth cameras offer a low-cost, portable solution but can produce inaccurate motion data.

    Purpose of the Study:

    • To introduce a rigid body modeling method to enhance the biological feasibility and accuracy of depth camera-based motion capture for upper limb function.
    • To evaluate the accuracy and repeatability of the modified reachable workspace (RW) and a new proximal function (PF) measure.
    • To compare depth camera performance with and without rigid body constraints against a gold-standard motion capture system.

    Main Methods:

    • Developed and applied a rigid body modeling technique to refine depth camera-tracked joint positions.
    • Assessed the reachable workspace (RW) and introduced a proximal function (PF) measure.
    • Evaluated accuracy and repeatability on ten asymptomatic subjects using both a low-cost depth camera and an active motion capture system.

    Main Results:

    • Rigid body constraints significantly improved the accuracy and concordance of depth camera measurements, especially during lateral reaching.
    • Both the enhanced RW and PF measures demonstrated feasibility for clinical assessment.
    • The study confirmed the potential of depth cameras with rigid body modeling for objective upper limb function evaluation.

    Conclusions:

    • Rigid body modeling enhances the reliability of depth camera-based upper limb function assessments.
    • The reachable workspace (RW) and proximal function (PF) measures are viable for clinical application.
    • Further research is needed to validate these measures in patient populations for detecting functional changes.