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: Jun 5, 2026

Bringing the Clinic Home: An At-Home Multi-Modal Data Collection Ecosystem to Support Adaptive Deep Brain Stimulation
06:32

Bringing the Clinic Home: An At-Home Multi-Modal Data Collection Ecosystem to Support Adaptive Deep Brain Stimulation

Published on: July 14, 2023

Validating Single-Camera Pose Estimation Against Multi-Camera Motion Capture for Accessible Biomechanical Assessment.

Aniket Pratapneni1,2, Ryan Halvorson1, Pavlos Silvestros1,3

  • 1Department of Orthopaedic Surgery, University of California, San Francisco, San Francisco, CA 94122, USA.

IEEE Access : Practical Innovations, Open Solutions
|June 4, 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

Large Language Model Predicts Surgeon Recommendations for Imaging and Surgery for Patients Presenting for Knee and Shoulder Complaints With 70% and 81% Accuracy Using Previsit Questionnaire Responses.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association·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

Prescreening depression using wearable electrocardiogram and photoplethysmogram data from a psycholinguistic experiment.

Physiological measurement·2025
Same author

3D motion capture data into a kinematic composite score for assessing musculoskeletal impairments.

Journal of biomechanics·2025
Same author

Early Biomechanical Recovery Following Total Hip Arthroplasty Is Associated With Preoperative Hip Muscle Fat-Fraction.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society·2025
Same journal

Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification.

IEEE access : practical innovations, open solutions·2026
Same journal

Radio-Frequency Toroid Susceptometry of Magnetic Nanoparticles: What Goes Around Comes Around.

IEEE access : practical innovations, open solutions·2026
Same journal

Cross-Architecture Knowledge Distillation for Histopathological Image Analysis.

IEEE access : practical innovations, open solutions·2026
Same journal

Mislabel Identification Using Transfer Learning-Based Ensemble Method.

IEEE access : practical innovations, open solutions·2026
Same journal

Deep Learning for Path Loss Prediction at 7 GHz in Urban Environment.

IEEE access : practical innovations, open solutions·2026
Same journal

A Translational Platform for Polyimide Neural Interfaces: Polyimide Synthesis and in Vivo Evaluation in Epileptic Mice.

IEEE access : practical innovations, open solutions·2026
See all related articles
This summary is machine-generated.

Single-camera pose estimation offers a low-cost, accessible alternative for motion analysis in musculoskeletal health. This study found it reliable for rehabilitation and telehealth, despite some accuracy limitations in dynamic movements.

Area of Science:

  • Biomechanics
  • Medical Technology
  • Rehabilitation Engineering

Background:

  • Musculoskeletal disorder diagnosis relies heavily on motion analysis.
  • Traditional multi-camera systems are costly, environment-specific, and require expertise.
  • Single-camera, deep-learning pose estimation presents a promising, accessible alternative.

Purpose of the Study:

  • To evaluate the clinical accuracy and reliability of a single-camera pose estimation model (MeTRAbs).
  • To compare MeTRAbs performance against a gold-standard multi-camera system (THEIA3D).
  • To assess feasibility for rehabilitation and telehealth applications.

Main Methods:

  • 51 participants performed gait, sit-to-stand, and trunk movements.
  • Simultaneous recording using a smartphone camera (30Hz) and THEIA3D (180Hz).
Keywords:
Biomechanicserror analysisgait and functional tasksjoint kinematicsmarkerless motion capturemonocular pose estimationrange of motionvalidation

Related Experiment Videos

Last Updated: Jun 5, 2026

Bringing the Clinic Home: An At-Home Multi-Modal Data Collection Ecosystem to Support Adaptive Deep Brain Stimulation
06:32

Bringing the Clinic Home: An At-Home Multi-Modal Data Collection Ecosystem to Support Adaptive Deep Brain Stimulation

Published on: July 14, 2023

  • Root-mean-square errors (RMSE) and Intraclass Correlation Coefficients (ICCs) analyzed accuracy and reliability.

    • Main Results:

    • Mean trajectory RMSE was 5.95 cm; joint angle RMSEs ranged from 2.10° to 10.98°.
    • Proximal joints and frontal plane motions showed higher accuracy.
    • Range of Motion ICCs exceeded 0.93, indicating strong reliability, with systematic bias identified as the main error source.

    Conclusions:

    • Single-camera pose estimation (MeTRAbs) demonstrates significant accuracy and reliability for clinical motion analysis.
    • It is a feasible and scalable tool for accessible rehabilitation and telehealth.
    • While not replacing multi-camera systems, it offers valuable insights for remote and outpatient settings.