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

Markerless motion capture methodologies in biomechanics: From 2D images to 3D joint angles, a narrative review.

Gait & posture·2026
Same author

Inverse optimal control of muscle force sharing during pathological gait.

Journal of biomechanics·2026
Same author

Are There Differences in Ankle Mechanics After Total Ankle Arthroplasty in Patients Suffering From Post-fracture vs Post-sprain End-Stage Ankle Osteoarthritis?

Foot & ankle international·2025
Same author

Development and laboratory evaluation of a markerless method to estimate low back intersegmental moments in childcare-related activities.

Journal of biomechanics·2025
Same author

Benchmarking raw datasets and collaboratively-evolving processed data for markerless motion capture analysis.

Data in brief·2025
Same author

A Confidence-Based Multibody Kinematics Optimization for Markerless Motion Capture: A Proof of Concept.

International journal for numerical methods in biomedical engineering·2025

Related Experiment Video

Updated: Dec 21, 2025

An Objective and Child-friendly Assessment of Arm Function by Using a 3-D Sensor
07:25

An Objective and Child-friendly Assessment of Arm Function by Using a 3-D Sensor

Published on: February 12, 2018

7.2K

Physically Consistent Whole-Body Kinematics Assessment Based on an RGB-D Sensor. Application to Simple Rehabilitation

Jessica Colombel1, Vincent Bonnet2, David Daney3

  • 1Université de Lorraine, CNRS, Inria, LORIA, F-54000 Nancy, France.

Sensors (Basel, Switzerland)
|May 21, 2020
PubMed
Summary

This study enhances joint angle accuracy using RGB-D sensors with a biomechanical model and Kalman filter. This approach enables accurate, physically consistent joint angle estimation for affordable in-home rehabilitation.

Keywords:
extended Kalman filter and rehabilitationmarkerless human motion analysis

More Related Videos

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.8K
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

Related Experiment Videos

Last Updated: Dec 21, 2025

An Objective and Child-friendly Assessment of Arm Function by Using a 3-D Sensor
07:25

An Objective and Child-friendly Assessment of Arm Function by Using a 3-D Sensor

Published on: February 12, 2018

7.2K
A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.8K
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

Area of Science:

  • Biomechanics
  • Rehabilitation Engineering
  • Sensor Technology

Background:

  • Accurate joint angle estimation is crucial for effective rehabilitation.
  • RGB-D sensors offer an affordable alternative to traditional motion capture systems.
  • Existing methods often lack physical consistency or require complex calibration.

Purpose of the Study:

  • To improve the accuracy of joint angle estimates from RGB-D sensors.
  • To develop a sensor-agnostic method for optimizing Kalman filter parameters.
  • To validate the proposed approach for in-home rehabilitation applications.

Main Methods:

  • Utilized a constrained extended Kalman Filter (EKF) incorporating a biomechanical model.
  • Developed a novel, sensor-independent method for optimal tuning of EKF covariance matrices using reference stereophotogrammetric data.
  • Performed statistical parametric mapping to compare optimal tuning with classical methods.

Main Results:

  • Achieved a satisfactory average root mean square difference of 9.7 degrees and a correlation coefficient of 0.8 for joint angle estimates across all joints.
  • Demonstrated the effectiveness of the biomechanical model in ensuring physically consistent joint angles and constant segment lengths.
  • Showcased significant improvement in covariance matrix tuning compared to classical methods.

Conclusions:

  • The proposed constrained biomechanical model and optimized EKF significantly improve joint angle estimation accuracy using affordable RGB-D sensors.
  • The developed tuning method is task-specific and requires tuning only once, making it practical for widespread use.
  • This approach supports the feasibility of using RGB-D sensors for simple, in-home rehabilitation monitoring.