Healthy Subjects or VolunteersIMU-GAITNCT07236008
Training and Testing Database for IMU Based Gait Analysis Methods
An observational study of Healthy Subjects or Volunteers, run by Vrije Universiteit Brussel at 1 site in Belgium.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 65 yearsHealthy volunteers can take part
- Conditions the study is for
- Healthy Subjects or Volunteers
- How many people
- 150 participants
- Where
- 1 siteBelgium
- Study dates
- 12 Dec 2025to 31 Dec 2029
- How long will I take part?
- 1 Day
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 65 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Healthy Adults, age 18-65
Who may be able to join
- Healthy subjects with no motor impairments that disrupt the walking pattern.
- No history of pain in the lower limbs in the past 6 months.
- No history of lower limbs injuries/surgeries in the past 6 months.
- Language: Dutch and/or English and/or French speakers.
- Age 18-65 years old
- Subjects must be able to understand the instructions and to answer questions. Additionally, they should be able to; signal pain, fear, discomfort; give inform consent.
Who cannot join
- Persons with comorbidity that could hinder the study (e.g.: unstable cardiovascular system disorders, lung disorders, severe osteoporosis).
- Individuals with metal implants or skin conditions that would make sensor or marker placement difficult.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Belgium1 site, 1 recruiting
- Recruiting
Faculty of Enginnering, ETRO department
Brussels, Belgium, 1050
Redona Brahimetaj, PhD engineering sciences, +32 2 629 20 10, redona.brahimetaj@vub.be
About this study
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.
Read the detailed description
This project investigates the development of accurate and reliable gait event (GE) detection methods using wearable inertial measurement units (IMUs), validated against goldstandard motion capture data (Vicon). Gait analysis plays a central role in understanding human locomotion and has important clinical applications in rehabilitation, neurology, orthopaedics, and fall-risk assessment. However, current IMU-based approaches are limited by synchronisation issues, small or homogeneous datasets, and insufficient validation against ground truth. This study addresses these gaps by systematically collecting and validating gait data in healthy participants. Data collection will be performed at the Brubotics Rehabilitation Research Center (BRRC) motion analysis laboratory. Participants will complete walking trials at different speeds (slow, self-selected, and fast speeds) along a standardised 10 m pathway. Reflective markers will be placed on anatomical landmarks, and a sacrum-mounted IMU will capture inertial signals. GE will be simultaneously recorded with the Vicon system, complemented by video and force plate data for validation. The study is organised into three phases. Phase 1 validates and refines Vicon-detected GE using complementary modalities. Phase 2 develops and evaluates deep learning algorithms for IMU-based detection, including the exploration of self-supervised learning. Phase 3 examines how differences in GE timing influence spatiotemporal gait parameters (e.g., step time, cadence, asymmetry), with the goal of establishing whether IMU-only systems can serve as reliable alternatives to motion capture. Ultimately, this project will deliver a robust dataset and algorithmic framework that improve the precision and generalisability of IMU-based GE detection.
- Conditions
- Healthy Subjects or Volunteers
- Keywords
- Gait analysis, Gait events, Spatiotemporal gait parameters (SGP), Inertial measurement units (IMU), Wearable sensors, Motion capture (Vicon), Deep learning, Machine learning, Healthy adults
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Healthy subjects | Age 18-65 years old |
What is being measured
The primary outcome is the main question the study is designed to answer.
Heel-Strike Timing Error: Force Plates vs Vicon
Absolute time difference between heel-strike detected by synchronized force plates (reference) and heel-strike detected by the Vicon motion-capture system. Force-plate heel-strike is defined as the first frame with vertical ground-reaction force.
Vicon heel-strike is the kinematic event labeled "heel-strike" per the lab's standard pipeline. Error is computed per step, then summarised as overall mean ± SD across participant(s). Lower values indicate better agreement.
Unit of Measure: milliseconds (ms)
Measured: 4 years
Toe-Off Timing Error: Force Plates vs Vicon
Absolute time difference between toe-off from force plates and toe-off detected by Vicon. Error is computed per step, averaged within participant, then summarized as overall mean ± SD. Lower values indicate better agreement.
Unit of Measure: milliseconds (ms)
Measured: 4 years
Event Agreement (%): Vicon vs Video - Heel-Strike
Percentage of heel-strike events for which Vicon and frame-by-frame video annotation indicate the same event within ms tolerance window (several tolerance windows will be explored). Agreement is computed per participant and summarized as mean ± SD across participant(s). Higher values indicate better agreement.
Unit of Measure: percent (%)
Measured: 4 years
Event Agreement (%): Vicon vs Video - Toe-Off
Percentage of toe-off events for which Vicon and video annotation match within a tolerance window (several tolerance windows will be assessed). Computed per participant; summarized as mean ± SD per participant(s). Higher values indicate better agreement.
Unit of Measure: percent (%)
Measured: 4 years
Secondary outcomes (14)
IMU Heel-Strike Detection Accuracy
Proportion of correctly classified heel-strike events by the IMU-based deep learning model relative to Vicon ground truth (correct classifications / total events), computed per participant and summarized as mean ± SD across participant(s).
Reference \& tolerance: Vicon event labels; a match is counted when IMU and Vicon events fall within same detection frame or within a tolerance window we will evaluate.
Unit of Measure: percent (%)
Measured: 4 years
Step Time Accuracy
Description: Absolute difference in step time between IMU-derived and Vicon-derived gait event detection. Step time is defined as the time between consecutive heel-strikes of opposite feet.
Unit of Measure: milliseconds (ms)
Measured: 4 years
IMU Toe-Off Detection Accuracy
Proportion of correctly classified toe off events by the IMU-based deep learning model relative to Vicon ground truth (correct classifications / total events), computed per participant and summarized as mean ± SD across participant(s).
Reference \& tolerance: Vicon event labels; a match is counted when IMU and Vicon events fall within same detection frame or within a tolerance window we will evaluate.
Unit of Measure: percent (%)
Measured: 4 years
IMU Heel-Strike Sensitivity (Recall)
True positives / (true positives + false negatives) for heel-strike detection vs Vicon, computed per participant(s); summarized as mean ± SD. Higher is better.
Unit of Measure: percent (%)
Reference \& tolerance: Vicon labels; match within a tolerance window to be analysed
Measured: 4
IMU Heel-Strike Specificity
True negatives / (true negatives + false positives) for heel-strike detection vs Vicon, computed per participant(s); summarized as mean ± SD. Higher is better.
Reference \& tolerance: Vicon labels; match within a tolerance window to be analysed
Unit of Measure: percent (%)
Measured: 4 years
IMU Toe-Off Sensitivity (Recall)
TP / (TP + FN) for toe-off detection vs Vicon, computed per participant(s); summarized as mean ± SD. Higher is better.
Reference \& tolerance: Vicon labels; match within a tolerance window to be analysed
Unit of Measure: percent (%)
Time Frame: 4 years
Measured: 4 years
IMU Toe-Off Specificity
TN / (TN + FP) for toe-off detection vs Vicon, computed per participant(s); summarized as mean ± SD. Higher is better.
Reference \& tolerance: Vicon labels; match within a tolerance window to be analysed
Unit of Measure: percent (%) Time Frame: 4 years
Measured: 4 years
Cadence Accuracy
Description: Absolute difference in cadence between IMU-derived and Vicon-derived measurements. Cadence is defined as the number of steps per minute.
Unit of Measure: steps per minute (steps/min)
Measured: 4 years
Step Length Accuracy
Description: Absolute difference in step length between IMU-derived and Vicon-derived measurements. Step length is defined as the distance between heel-strikes of opposite feet.
Unit of Measure: meters (mm)
Measured: 4 years
Step-Time Asymmetry Accuracy
Description: Absolute difference in step-time asymmetry index between IMU-derived and Vicon-derived data. The asymmetry index is calculated as the relative difference between left and right step times.
Unit of Measure: percent (%)
Measured: 4 years
Stride Time Accuracy
Description: Absolute difference in stride time between IMU-derived and Vicon-derived data. Stride time is defined as the time between heel-strikes of the same foot.
Unit of Measure: milliseconds (ms)
Measured: 4 years
Stride Length Accuracy
Description: Absolute difference in stride length between IMU-derived and Vicon-derived measurements. Stride length is defined as the distance between consecutive heel-strikes of the same foot.
Unit of Measure: meters (mm)
Measured: 4 years
Stance Time Accuracy
Description: Absolute difference in stance time between IMU-derived and Vicon-derived data. Stance time is defined as the time from heel-strike to toe-off of the same foot.
Unit of Measure: milliseconds (ms)
Measured: 4 years
Double-Support Time Accuracy
Description: Absolute difference in double-support time between IMU-derived and Vicon-derived measurements. Double-support time refers to the duration during which both feet are in contact with the ground.
Unit of Measure: milliseconds (ms)
Measured: 4 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Nov 2025
- Study start12 Dec 2025
- Primary completion31 Dec 2029 (estimated)
- Study completion31 Dec 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Healthy Subjects or VolunteersStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 150 participants (estimated)
- Target duration
- 1 Day
Sponsor and investigators
- Lead sponsor
- Vrije Universiteit Brussel
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Bart Jansen, Vrije Universiteit Brussel
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07236008
- Sponsor's protocol ID
- 25235_IMU-GAIT
- Other IDs
- 25235
- Acronym
- IMU-GAIT
- Status last verified
- Aug 2026
- First submitted
- 27 Aug 2025
- Last updated
- 19 Aug 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: Still undecided
Study at a glance
From the registry record, last updated by the sponsor on 19 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Training and Testing Database for IMU Based Gait Analysis Methods
- ClinicalTrials.gov ID
- NCT07236008
- Acronym / sponsor ID
- IMU-GAIT / 25235_IMU-GAIT
- Conditions
- Healthy Subjects or Volunteers
- Keywords
- Gait analysis, Gait events, Spatiotemporal gait parameters (SGP), Inertial measurement units (IMU), Wearable sensors, Motion capture (Vicon), Deep learning, Machine learning
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 150 participants (estimated)
- Lead sponsor
- Vrije Universiteit BrusselUniversity, hospital or other
- Study start
- 12 Dec 2025 (actual)
- Primary completion
- 31 Dec 2029 (estimated)
- Study completion
- 31 Dec 2029 (estimated)
- First posted
- 19 Nov 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
This project investigates the development of accurate and reliable gait event (GE) detection methods using wearable inertial measurement units (IMUs), validated against goldstandard motion capture data (Vicon). Gait analysis plays a central role in understanding human locomotion and has important clinical applications in rehabilitation, neurology, orthopaedics, and fall-risk assessment. However, current IMU-based approaches are limited by synchronisation issues, small or homogeneous datasets, and insufficient validation against ground truth. This study addresses these gaps by systematically collecting and validating gait data in healthy participants. Data collection will be performed at the Brubotics Rehabilitation Research Center (BRRC) motion analysis laboratory. Participants will complete walking trials at different speeds (slow, self-selected, and fast speeds) along a standardised 10 m pathway. Reflective markers will be placed on anatomical landmarks, and a sacrum-mounted IMU will capture inertial signals. GE will be simultaneously recorded with the Vicon system, complemented by video and force plate data for validation. The study is organised into three phases. Phase 1 validates and refines Vicon-detected GE using complementary modalities. Phase 2 develops and evaluates deep learning algorithms for IMU-based detection, including the exploration of self-supervised learning. Phase 3 examines how differences in GE timing influence spatiotemporal gait parameters (e.g., step time, cadence, asymmetry), with the goal of establishing whether IMU-only systems can serve as reliable alternatives to motion capture. Ultimately, this project will deliver a robust dataset and algorithmic framework that improve the precision and generalisability of IMU-based GE detection.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 1 Day
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Healthy subjects | – | –Age 18-65 years old |
Who may qualify
- Ages
- 18 to 65 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Healthy Adults, age 18-65
Key inclusion criteria (6 listed)
- Healthy subjects with no motor impairments that disrupt the walking pattern.
- No history of pain in the lower limbs in the past 6 months.
- No history of lower limbs injuries/surgeries in the past 6 months.
- Language: Dutch and/or English and/or French speakers.
- Age 18-65 years old
Key exclusion criteria (2 listed)
- Persons with comorbidity that could hinder the study (e.g.: unstable cardiovascular system disorders, lung disorders, severe osteoporosis).
- Individuals with metal implants or skin conditions that would make sensor or marker placement difficult.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Heel-Strike Timing Error: Force Plates vs Vicon
Time frame: 4 years
Absolute time difference between heel-strike detected by synchronized force plates (reference) and heel-strike detected by the Vicon motion-capture system. Force-plate heel-strike is defined as the first frame with vertical ground-reaction force. Vicon heel-strike is the kinematic event labeled "heel-strike" per the lab's standard pipeline. Error is computed per step, then summarised as overall mean ± SD across participant(s). Lower values indicate better agreement. Unit of Measure: milliseconds (ms)
Toe-Off Timing Error: Force Plates vs Vicon
Time frame: 4 years
Absolute time difference between toe-off from force plates and toe-off detected by Vicon. Error is computed per step, averaged within participant, then summarized as overall mean ± SD. Lower values indicate better agreement. Unit of Measure: milliseconds (ms)
Event Agreement (%): Vicon vs Video - Heel-Strike
Time frame: 4 years
Percentage of heel-strike events for which Vicon and frame-by-frame video annotation indicate the same event within ms tolerance window (several tolerance windows will be explored). Agreement is computed per participant and summarized as mean ± SD across participant(s). Higher values indicate better agreement. Unit of Measure: percent (%)
Event Agreement (%): Vicon vs Video - Toe-Off
Time frame: 4 years
Percentage of toe-off events for which Vicon and video annotation match within a tolerance window (several tolerance windows will be assessed). Computed per participant; summarized as mean ± SD per participant(s). Higher values indicate better agreement. Unit of Measure: percent (%)
14 secondary outcomes
IMU Heel-Strike Detection Accuracy
Time frame: 4 years
Step Time Accuracy
Time frame: 4 years
IMU Toe-Off Detection Accuracy
Time frame: 4 years
IMU Heel-Strike Sensitivity (Recall)
Time frame: 4
IMU Heel-Strike Specificity
Time frame: 4 years
IMU Toe-Off Sensitivity (Recall)
Time frame: 4 years
IMU Toe-Off Specificity
Time frame: 4 years
Cadence Accuracy
Time frame: 4 years
Step Length Accuracy
Time frame: 4 years
Step-Time Asymmetry Accuracy
Time frame: 4 years
Stride Time Accuracy
Time frame: 4 years
Stride Length Accuracy
Time frame: 4 years
Stance Time Accuracy
Time frame: 4 years
Double-Support Time Accuracy
Time frame: 4 years
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Aug 2026.
- Individual participant dataSharing planned: Undecided. Still undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Healthy Subjects or Volunteers, run by Vrije Universiteit Brussel at 1 site in Belgium.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 19 Aug 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Belgium. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Redona Brahimetaj, Doctor of Engineering Sciences (0032465597448, redona.brahimetaj@vub.be), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Heel-Strike Timing Error: Force Plates vs Vicon (time frame: 4 years). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Aug 2026.