HealthyNCT07451509
Implementation of Machine Learning Into Optical Pedography
An observational study of Healthy and Foot, run by Palacky University at 1 site in Czechia.
Trial summary
This study aims to evaluate the validity and reliability of a proposed plantar pressure assessment intrument based on an implementation of machine learning into optical pedography. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Healthy, Foot, Pressure Area
- What is being tested?
- Optical pedography
- How many people
- 150 participants
- Where
- 1 siteCzechia
- Study dates
- 14 Sep 2026to Dec 2027
- 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 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Healthy individuals willing to participate in the study protocol
Who may be able to join
- A healthy individual with no absence of lower extremity
- Aged ≥18 years
- Willingness to participate and ability to follow the assessors instructions.
Who cannot join
- Presence of foot diseases alternating foot contact area
- Cognitive or psychiatric disorders limiting cooperation
- Lack of informed consent or non-compliance during imaging
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Czechia1 site, 1 recruiting
- Recruiting
Faculty of Health Sciences, Palacký University Olomouc, Czech Republic
Olomouc, Czechia, 77900
Jonatan Dvořáček, +420731061089, jonatan.dvoracek01@upol.cz
Jonatan Dvořáček
About this study
Official title: Implementing Machine Learning Into Optical Pedography: Development and Validation of a Novel Instrument: a Validation Study
This study aims to evaluate the validity and reliability of a proposed plantar pressure assessment intrument based on an implementation of machine learning into optical pedography.
Read the detailed description
This study aims to evaluate the validity and reliability of a proposed plantar pressure assessment intrument based on an implementation of machine learning into optical pedography. The whole process will be divided into distinct steps required for the targeted outcome, which includes:
- collecting visual data (podoscope foot pictures) and training a segmentation machine learning-based algorithm designed for recognizing only feet area, a total of atleast 30 participants performing 9 different standing positions - over 270 usable pictures for training and functionality validation
- collecting personal, visual and pressure data (participant weight, podoscope foot pictures, pedobarographic platform measurements) and training a machine/deep learning-based model designed for feet pressure distribution areas identification and quantification, a total of estimated 60 participants undergoing 5 alternating, as similar as possible, measurements on podoscope and pedobarographic platform
- evaluating the validity and reliability of a new plantar pressure measuring instrument following the same imaging procedure as described in step 2, a total of estimated 60 participants
- Conditions
- Healthy, Foot, Pressure Area, Pressure Distribution
- Being tested
- Optical pedography
- Keywords
- pedography, machine learning, AI, plantar pressure, validity, reliability
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Optical pedographyDiagnostic test
Comparison of 5 alternating measures taken on podoscope and pedobarographic platform
What is being measured
The primary outcome is the main question the study is designed to answer.
Criterion validity of foot area measurement
The total contact area of the foot during a static stance will be measured by the machine learning based optical pedography Instrument and compared to the gold standard pedobarographic platform. The validity will be determined by the Pearson Correlation Coefficient (r) between the two devices. Unit of measure: Pearson Correlation Coefficient (r) ranging from -1 to 1.
Measured: Day 1
Criterion validity of peak plantar pressure distribution
The distribution of pressure across the plantar surface (specifically mean peak pressure) will be measured. Validity will be assessed by calculating the Intraclass Correlation Coefficient (ICC) between the machine learning based optical pedography instrument and the gold standard pedobarographic platform. Unit of measure: Intraclass Correlation Coefficient (ICC) ranging from 0 to 1.
Measured: Day 1
Intrasession reliability of foot area measurement
The consistency of the total contact area (cm 2) measured across 5 repeated trials within a single session. Reliability will be assessed using the Intraclass Correlation Coefficient (ICC 3,5) to determine the degree of agreement between the five captures of the same participant's feet. Units of measure: Intraclass Correlation Coefficient (ICC) ranging from 0 to 1
Measured: Day 1
Intrasession reliability of mean peak pressure
The consistency of mean peak pressure measurements across 5 repeated trials within a single session. Reliability will be assessed by calculating the Intraclass Correlation Coefficient (ICC 3,5) for the five measurements taken on the machine learning based optical pedography instrument. Unit of measure: Intraclass Correlation Coefficient (ICC) ranging from 0 to 1
Measured: Day 1
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 Mar 2026
- Study start14 Sep 2026
- Primary completionJul 2027 (estimated)
- Study completionDec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for HealthyStudies 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
- Other
- Time perspective
- Prospective
- Enrolment
- 150 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Palacky University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Jonatan Dvoracek, Palacky University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07451509
- Sponsor's protocol ID
- UPOL-340091/1030S-2025
- Status last verified
- Feb 2026
- First submitted
- 11 Feb 2026
- Last updated
- 17 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data will not be shared due to patient privacy and institutional data protection policies
Study at a glance
From the registry record, last updated by the sponsor on 17 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Implementing Machine Learning Into Optical Pedography: Development and Validation of a Novel Instrument: a Validation Study
- ClinicalTrials.gov ID
- NCT07451509
- Acronym / sponsor ID
- UPOL-340091/1030S-2025
- Conditions
- Healthy, Foot, Pressure Area, Pressure Distribution
- Keywords
- pedography, machine learning, AI, plantar pressure, validity, reliability
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 150 participants (estimated)
- Lead sponsor
- Palacky UniversityUniversity, hospital or other
- Study start
- 14 Sep 2026 (actual)
- Primary completion
- Jul 2027 (estimated)
- Study completion
- Dec 2027 (estimated)
- First posted
- 5 Mar 2026 (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.
This study aims to evaluate the validity and reliability of a proposed plantar pressure assessment intrument based on an implementation of machine learning into optical pedography.
Detailed description
This study aims to evaluate the validity and reliability of a proposed plantar pressure assessment intrument based on an implementation of machine learning into optical pedography. The whole process will be divided into distinct steps required for the targeted outcome, which includes:
- collecting visual data (podoscope foot pictures) and training a segmentation machine learning-based algorithm designed for recognizing only feet area, a total of atleast 30 participants performing 9 different standing positions - over 270 usable pictures for training and functionality validation
- collecting personal, visual and pressure data (participant weight, podoscope foot pictures, pedobarographic platform measurements) and training a machine/deep learning-based model designed for feet pressure distribution areas identification and quantification, a total of estimated 60 participants undergoing 5 alternating, as similar as possible, measurements on podoscope and pedobarographic platform
- evaluating the validity and reliability of a new plantar pressure measuring instrument following the same imaging procedure as described in step 2, a total of estimated 60 participants
Study design
- Observational model
- Other
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Healthy individuals willing to participate in the study protocol
Key inclusion criteria (3 listed)
- A healthy individual with no absence of lower extremity
- Aged ≥18 years
- Willingness to participate and ability to follow the assessors instructions.
Key exclusion criteria (3 listed)
- Presence of foot diseases alternating foot contact area
- Cognitive or psychiatric disorders limiting cooperation
- Lack of informed consent or non-compliance during imaging
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Optical pedographyComparison of 5 alternating measures taken on podoscope and pedobarographic platform | Diagnostic test | – |
Primary outcome
Criterion validity of foot area measurement
Time frame: Day 1
The total contact area of the foot during a static stance will be measured by the machine learning based optical pedography Instrument and compared to the gold standard pedobarographic platform. The validity will be determined by the Pearson Correlation Coefficient (r) between the two devices. Unit of measure: Pearson Correlation Coefficient (r) ranging from -1 to 1.
Criterion validity of peak plantar pressure distribution
Time frame: Day 1
The distribution of pressure across the plantar surface (specifically mean peak pressure) will be measured. Validity will be assessed by calculating the Intraclass Correlation Coefficient (ICC) between the machine learning based optical pedography instrument and the gold standard pedobarographic platform. Unit of measure: Intraclass Correlation Coefficient (ICC) ranging from 0 to 1.
Intrasession reliability of foot area measurement
Time frame: Day 1
The consistency of the total contact area (cm 2) measured across 5 repeated trials within a single session. Reliability will be assessed using the Intraclass Correlation Coefficient (ICC 3,5) to determine the degree of agreement between the five captures of the same participant's feet. Units of measure: Intraclass Correlation Coefficient (ICC) ranging from 0 to 1
Intrasession reliability of mean peak pressure
Time frame: Day 1
The consistency of mean peak pressure measurements across 5 repeated trials within a single session. Reliability will be assessed by calculating the Intraclass Correlation Coefficient (ICC 3,5) for the five measurements taken on the machine learning based optical pedography instrument. Unit of measure: Intraclass Correlation Coefficient (ICC) ranging from 0 to 1
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 17 Sep 2026.
- Individual participant dataSharing planned: No. Individual participant data will not be shared due to patient privacy and institutional data protection policies
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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 and Foot, run by Palacky University at 1 site in Czechia.
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 3 inclusion and 3 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 17 Sep 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 Czechia. 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 Jonatan Dvořáček (+420731061089, jonatan.dvoracek01@upol.cz), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Criterion validity of foot area measurement (time frame: Day 1). 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 17 Sep 2026.