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Training and Testing Database for IMU Based Gait Analysis Methods

NCT07236008 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 150

Last updated 2025-11-19

No results posted yet for this study

Summary

The goal of this study is to establish a high-quality, synchronised dataset of gait events (GE) by simultaneously collecting inertial measurement unit (IMU) data and validated ground truth detections using a Vicon motion capture system. The primary objective is to address existing limitations in GE detection - such as poor generalisability, limited data diversity, and lack of precise synchronisation - through a rigorous protocol that ensures accuracy and transparency. The experiment is structured in three phases. First, Vicon-derived GE will be validated and refined using complementary modalities (force plates and video recordings). Next, deep learning (DL) algorithms will be developed and evaluated for GE detection directly from IMU data, with Vicon annotations serving as ground truth. Finally, the impact of differences in GE timing on spatiotemporal gait parameters (SGP) will be analysed to assess the feasibility of using IMU-only systems for reliable gait analysis.

By achieving these objectives, the study aims to improve the accuracy of GE detection from wearable sensors and enable more accessible, scalable, and reliable gait analysis outside the laboratory environment.

Conditions

  • Healthy Subjects or Volunteers

Sponsors & Collaborators

  • Vrije Universiteit Brussel

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
65 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-12-01
Primary Completion
2029-11-30
Completion
2029-12-31

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07236008 on ClinicalTrials.gov