Jove
Visualize
Contact Us

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

Long-Term Ravulizumab Efficacy and Safety in AQP4 Antibody-Positive Neuromyelitis Optica Spectrum Disorder: Final CHAMPION-NMOSD Results.

Neurology(R) neuroimmunology & neuroinflammation·2026
Same author

Factors Associated With Disability Improvement and Worsening Independent of Attacks in Patients With AQP4-IgG+ NMOSD and MOGAD: A Multicenter Cohort Study.

Neurology·2026
Same author

Relative frequencies of muscle specific kinase antibody myasthenia in 46 centres worldwide.

Brain : a journal of neurology·2026
Same author

Immuno-Proteomic Features Associated to Relapse Risk in Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease.

Neurology(R) neuroimmunology & neuroinflammation·2026
Same author

Simultaneous T<sub>2</sub>, T<sub>2</sub>*, and R<sub>2</sub>' Mapping for Multiple Sclerosis Using Nonlinear Model-Based Reconstruction of Undersampled Radial RARE-EPI MRI.

Magnetic resonance in medicine·2026
Same author

The exercise hormone irisin has neuroprotective effects in a mouse model of multiple sclerosis.

Nature metabolism·2026
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: Sep 28, 2025

Movement Retraining using Real-time Feedback of Performance
08:16

Movement Retraining using Real-time Feedback of Performance

Published on: January 17, 2013

13.5K

Proposal for Post Hoc Quality Control in Instrumented Motion Analysis Using Markerless Motion Capture: Development

Hanna Marie Röhling1,2,3,4, Patrik Althoff1,2,3, Radina Arsenova1,2,3,5

  • 1Experimental and Clinical Research Center, a cooperation between the Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association and the Charité - Universitätsmedizin Berlin, Berlin, Germany.

JMIR Human Factors
|April 1, 2022
PubMed
Summary

A new quality control (QC) pipeline for markerless motion capture technology ensures reliable motor symptom assessment in movement disorders. This system enhances data quality for clinical use and future research.

Keywords:
gait analysisinstrumented motion analysismarkerless motion capturequality controlquality reportingvisual perceptive computing

More Related Videos

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
08:24

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

Published on: August 30, 2016

10.4K
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

10.8K

Related Experiment Videos

Last Updated: Sep 28, 2025

Movement Retraining using Real-time Feedback of Performance
08:16

Movement Retraining using Real-time Feedback of Performance

Published on: January 17, 2013

13.5K
Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
08:24

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

Published on: August 30, 2016

10.4K
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

10.8K

Area of Science:

  • Biomedical Engineering
  • Clinical Neurology
  • Rehabilitation Technology

Background:

  • Instrumented assessment of motor symptoms offers a promising extension to clinical evaluation for movement disorders.
  • Markerless motion capture technologies present a scalable, cost-effective solution for large-scale application.
  • Standardized tools are essential for quality control to integrate these technologies into clinical routine.

Purpose of the Study:

  • Develop a systematic quality control (QC) procedure for markerless motion capture data.
  • Implement and experimentally validate the QC procedure to identify quality concerns.
  • Rate the usability of motor task recordings using the developed QC pipeline.

Main Methods:

  • A post hoc QC pipeline was developed and evaluated on a large dataset of motor task recordings.
  • Recordings from healthy controls and individuals with multiple sclerosis were analyzed.
  • Two independent raters applied the pipeline, assessing usability and identifying technical/performance quality concerns.

Main Results:

  • The QC pipeline demonstrated user-friendliness and large-scale applicability.
  • Rater agreement on recording usability ranged from 71.5% to 92.3% across different motor tasks.
  • Satisfactory quality ratings were achieved in 39.6%-85.1% of recordings, with 5.0%-26.3% being discarded by both raters.

Conclusions:

  • A feasible and useful QC pipeline for clinical quality screening of markerless motion capture data was presented.
  • The study highlights the necessity of QC, even with standardized setups and training.
  • The QC process aids in data cleaning, quality assurance optimization, and development of automated QC approaches for improved kinematic data reliability.