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Updated: May 11, 2026

Home-Based Monitor for Gait and Activity Analysis

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

Inertial sensor-based two feet motion tracking for gait analysis.

Tran Nhat Hung¹, Young Soo Suh

¹Department of Electrical Engineering, University of Ulsan, Namgu, Ulsan 680-749, Korea. hungtn306@gmail.com

Sensors (Basel, Switzerland)

|May 1, 2013

Summary

This study presents a novel system for gait analysis using inertial sensors on shoes. The system accurately estimates foot motion, providing key parameters for walking analysis.

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Area of Science:

Biomechanics
Wearable Technology
Motion Analysis

Background:

Gait analysis is crucial for understanding human locomotion and diagnosing movement disorders.
Accurate estimation of foot motion is essential for reliable gait analysis.
Existing methods may have limitations in accuracy or practicality for everyday use.

Purpose of the Study:

To develop and validate a novel system for estimating two-feet motion for comprehensive gait analysis.
To integrate inertial sensors and a camera-based system for precise inter-shoe position error correction.
To extract key gait parameters and three-dimensional foot trajectories.

Main Methods:

Attaching inertial sensors to each shoe to estimate individual foot movement.
Employing an inertial navigation algorithm for motion tracking.

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Home-Based Monitor for Gait and Activity Analysis

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Published on: August 8, 2019

3D Kinematic Gait Analysis for Preclinical Studies in Rodents

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Utilizing a camera on the right shoe and infrared LEDs on the left shoe to correct inter-shoe positional errors.

Main Results:

The system successfully estimates the motion of both feet during walking.
Key gait analysis parameters including step length, stride length, foot angle, and walking speed are accurately provided.
Three-dimensional trajectories of both feet are generated for detailed gait analysis.

Conclusions:

The proposed system offers a practical and accurate solution for gait analysis.
Integration of inertial sensors and vision-based correction enhances the reliability of foot motion estimation.
This technology has potential applications in clinical settings, sports science, and rehabilitation.