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

Measuring Acceleration Due to Gravity01:12

Measuring Acceleration Due to Gravity

608
Consider a coffee mug hanging on a hook in a pantry. If the mug gets knocked, it oscillates back and forth like a pendulum until the oscillations die out.
A simple pendulum can be described as a point mass and a string. Meanwhile, a physical pendulum is any object whose oscillations are similar to a simple pendulum, but cannot be modeled as a point mass on a string because its mass is distributed over a larger area. The behavior of a physical pendulum can be modeled using the principles of...
608

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Biomechanical Assessment of Functional Tasks Beyond Level Walking Following Total Hip Arthroplasty: A Scoping Review.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society·2026
Same author

Patient-specific versus off-the-shelf unicompartmental knee arthroplasty during level walking.

Journal of experimental orthopaedics·2025
Same author

The Impact of Osteoarthritis-Specific Anatomical Features and Gait Patterns on Medial Compartment Loading in the Presence of Ligament Laxity.

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

Validity and Reliability of Inertial Motion Unit-Based Performance Metrics During Wheelchair Racing Propulsion.

Sensors (Basel, Switzerland)·2025
Same author

Population-based in silico modeling of anatomical shape variation of the knee and its impact on joint loading in knee osteoarthritis.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society·2024
Same author

The Overlay, a New Solution for Volume Variations in the Residual Limb for Individuals with a Transtibial Amputation.

Sensors (Basel, Switzerland)·2024

Related Experiment Video

Updated: Aug 9, 2025

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
10:52

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Published on: April 13, 2016

8.9K

Inertial Sensor Location for Ground Reaction Force and Gait Event Detection Using Reservoir Computing in Gait.

Sara Havashinezhadian1, Laurent Chiasson-Poirier2, Julien Sylvestre2

  • 1Interdisciplinary Center for Research in Rehabilitation and Social Integration (CIRRIS), Department of Kinesiology, Faculty of Medicine, Université Laval, Quebec, QC G1V 0A6, Canada.

International Journal of Environmental Research and Public Health
|February 25, 2023
PubMed
Summary

The top of the shoe is the optimal location for inertial measurement units (IMUs) to accurately predict gait event detection (GED) and ground reaction forces (GRF) in both healthy individuals and those with medial knee osteoarthritis (MKOA). This finding aids in non-invasive gait analysis.

Keywords:
gait event detectionground reaction forceinertial measurement unitreservoir computingsensor location

More Related Videos

Home-Based Monitor for Gait and Activity Analysis
07:24

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

6.8K
Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings
06:21

Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings

Published on: July 26, 2022

2.6K

Related Experiment Videos

Last Updated: Aug 9, 2025

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
10:52

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Published on: April 13, 2016

8.9K
Home-Based Monitor for Gait and Activity Analysis
07:24

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

6.8K
Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings
06:21

Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings

Published on: July 26, 2022

2.6K

Area of Science:

  • Biomechanics
  • Wearable Technology
  • Medical Engineering

Background:

  • Inertial measurement units (IMUs) offer a promising non-invasive method for gait analysis.
  • Accurate gait event detection (GED) and ground reaction force (GRF) estimation are crucial for diagnosing and managing conditions like medial knee osteoarthritis (MKOA).
  • Optimal sensor placement is key to maximizing the accuracy of IMU-based gait analysis.

Purpose of the Study:

  • To identify the most effective sensor location on the lower limb for predicting GED and GRF using IMUs.
  • To compare sensor performance between healthy individuals and those with MKOA.
  • To validate the use of reservoir computing for gait analysis with IMU data.

Main Methods:

  • Utilized data from 27 healthy and 18 MKOA participants walking on an instrumented treadmill at various speeds.
  • Deployed five synchronized IMUs on the lower limb (shoe, heel, ankle, tibia, shank).
  • Trained an artificial neural network (reservoir computing) using acceleration signals from IMUs to predict GRF and GED.

Main Results:

  • The top of the shoe emerged as the best sensor location for GRF prediction in 72.2% of healthy individuals and 41.7% of MKOA individuals, based on minimum mean absolute error (MAE).
  • For GED, the middle and front of the tibia, followed by the top of the shoe, yielded the minimum MAE for both participant groups.
  • The study indicates that the top of the shoe is a universally effective location for both GED and GRF prediction.

Conclusions:

  • Sensor placement significantly impacts the accuracy of IMU-based gait analysis for both GED and GRF.
  • The top of the shoe represents a highly effective location for IMU placement for comprehensive gait analysis in healthy and MKOA populations.
  • These findings can inform the development of more accurate and accessible wearable gait monitoring systems.