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

Monocular Markerless Motion Capture Enables Quantitative Assessment of Upper Extremity Reachable Workspace.

Sensors (Basel, Switzerland)·2026
Same author

Assessing the Validity of Whole-Body and Segmental Angular Momenta During Walking in Older Individuals With and Without Transtibial Limb Loss.

Journal of applied biomechanics·2026
Same author

Characterizing the interaction effects of modular components on transtibial prosthesis stance-phase mechanical behavior.

Prosthetics and orthotics international·2025
Same author

Changes in Dynamic Mean Ankle Moment Arm in Unimpaired Walking Across Speeds, Ramps, and Stairs.

Journal of biomechanical engineering·2024
Same author

Categorization and recommendations for outcome measures for lower limb absence by an expert panel.

Prosthetics and orthotics international·2023
Same author

Validating a fear-of-falling-related activity avoidance scale in lower limb prosthesis users.

PM & R : the journal of injury, function, and rehabilitation·2023

Related Experiment Video

Updated: May 17, 2025

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

524

An Open-Source Wearable System for Real-Time Human Biomechanical Analysis.

Zachary Hoegberg1,2,3, Seth Donahue1,2,4,5, Matthew J Major1,2,6,7

  • 1Department of Physical Medicine & Rehabilitation, Northwestern University, Chicago, IL 60611, USA.

Sensors (Basel, Switzerland)
|May 14, 2025
PubMed
Summary

This study introduces an accessible multi-inertial measurement unit (IMU) system for motion analysis, overcoming clinical adoption barriers. The system offers streamlined calibration and real-time gait biofeedback, enhancing patient-facing applications.

Keywords:
gait rehabilitationinertial measurement unitmotion analysiswearable sensors

More Related Videos

A Real-Time Wearable Electromyography Measurement System for Small Animals
05:00

A Real-Time Wearable Electromyography Measurement System for Small Animals

Published on: November 15, 2024

510
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.6K

Related Experiment Videos

Last Updated: May 17, 2025

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

524
A Real-Time Wearable Electromyography Measurement System for Small Animals
05:00

A Real-Time Wearable Electromyography Measurement System for Small Animals

Published on: November 15, 2024

510
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.6K

Area of Science:

  • Biomechanics
  • Wearable Technology
  • Clinical Engineering

Background:

  • Inertial Measurement Unit (IMU) technology offers potential for motion analysis.
  • Clinical adoption of IMUs is limited by cost, setup complexity, and expertise requirements.
  • Existing proprietary systems hinder accessibility in patient-facing applications.

Purpose of the Study:

  • To develop and present a multi-IMU system designed for accessible and efficient motion analysis.
  • To address the constraints of cost, setup time, and specialized knowledge in clinical IMU use.
  • To enable patient-facing applications through streamlined calibration and data processing.

Main Methods:

  • Development of a multi-IMU system with modular design for adaptability.
  • Implementation of streamlined calibration protocols and efficient data processing.
  • Focus on user-friendly software deployment for clinical and rehabilitation settings.

Main Results:

  • Demonstration of near-real-time measurement of lower-limb gait kinematics.
  • Provision of stride-to-stride biofeedback using a single sensor.
  • Successful adaptation for diverse motion tracking scenarios beyond initial gait analysis.

Conclusions:

  • The developed multi-IMU system shows significant potential for gait assessment and rehabilitation.
  • The system's accessibility and efficiency can overcome barriers to clinical adoption of IMU technology.
  • Future validation against optical motion capture methods is planned to further establish its utility.