- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06433024
Training of a Artificial Intelligence Model to Detect Venous Diseases Using PPG Technology
May 29, 2024 updated by: The Whiteley Clinic
A Pilot Study Using AI Algorithms and PPG Technology for the Detection of Venous Diseases
This clinical research aims to evaluate the effectiveness of using Photoplethysmography (PPG) signals combined with Artificial Intelligence (AI) algorithms, for the precise classification and diagnosis of Venous Diseases of the lower limb.
This study invites a group of participants who currently undergoing investigations for venous disease at The Whiteley Clinic (hereinafter referred to as TWC).
The Participants will be classified into control (healthy individuals with no significant venous disease) and chronic venous disease (CVD) (diagnosed with proven venous disease) groups.
Prospective participants who express an interest in being included in the study will be given a patient information sheet and will undergo a briefing of the pilot study.
If they consent and sign the relevant consent forms, the participants will perform a series of standardized exercises under the supervision of a consultant vascular surgeon.
Throughout the exercises, a data acquisition device attached to the ankle records the PPG signals, capturing the changes in blood volume due to the reflected PPG signals from the red blood cells during the movement.
Thus, once the data is collected and recorded, this allows for the analysis of the data of the control group and CVD group against each other.
During the analysis of the two groups' PPG signals, the objective lies within the capability to detect subtle nuances in the patterns of the PPG signals during the performed movements using AI algorithms.
The AI algorithms will distinguish patterns or features indicating the presence or absence of venous disease.
This study seeks to contribute valuable insights into enhancing the diagnosis of venous disease using PPG and AI algorithms, paving novel approaches to Venous healthcare.
Study Overview
Status
Not yet recruiting
Conditions
Intervention / Treatment
Study Type
Observational
Enrollment (Estimated)
20
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Contact
- Name: Sergio Da Silva, PhD
- Phone Number: 01483477199
- Email: people@thewhiteleyclinic.co.uk
Study Contact Backup
- Name: Serah Duro, MSc
- Email: serah.duro@thewhiteleyclinic.co.uk
Study Locations
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Guildford, United Kingdom, GU2 7RF
- The Whiteley Clinic
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Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Yes
Sampling Method
Non-Probability Sample
Study Population
This study invites a group of participants who have attended The Whiteley Clinic (hereinafter referred to as TWC).
The Participants are split into control (healthy individuals) and treatment (previously diagnosed with Venous disease) groups.
Description
Inclusion Criteria:
- Patients are attending for investigation of suspected venous disease. Patients must be able to walk and mobile normally and have good skin integrity of the lower leg, where the PPG is attached.
All patients attending TWC are 18 years or older.
Exclusion Criteria:
- Subjects with known arterial occlusive disease or physical disability affecting gait or ankle movement will be excluded.
Patients unable to have a PPG attached to the lower leg (ie: active ulceration) will be excluded.
Patients unable to give consent. Pregnant female.
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
|
Individuals with CVD (Treatment Group)
Participants who have been diagnosed with Chronic Venous Disease (CVD).
|
The study investigates venous competence through three distinct exercises using photoplethysmography (PPG) technology to record blood flow in the leg veins of 20 subjects, split into two groups: those with chronic venous disease (CVD) and those without.
The null hypothesis is that there will be no significant difference in venous filling times (VFT) and PPG trace variations between subjects with CVD and those without under different physical conditions.
The alternative hypothesis suggests that individuals with CVD will show distinct PPG patterns, particularly shorter VFT and varied pressure changes, indicative of venous reflux or obstruction.
This hypothesis is chosen based on prior evidence suggesting observable differences in venous function between affected and non-affected individuals.
|
|
Individuals Without CVD (Control Group)
Participants who have not been diagnosed with CVD.
|
The study investigates venous competence through three distinct exercises using photoplethysmography (PPG) technology to record blood flow in the leg veins of 20 subjects, split into two groups: those with chronic venous disease (CVD) and those without.
The null hypothesis is that there will be no significant difference in venous filling times (VFT) and PPG trace variations between subjects with CVD and those without under different physical conditions.
The alternative hypothesis suggests that individuals with CVD will show distinct PPG patterns, particularly shorter VFT and varied pressure changes, indicative of venous reflux or obstruction.
This hypothesis is chosen based on prior evidence suggesting observable differences in venous function between affected and non-affected individuals.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Diagnostic Accuracy of an AI Model for Venous Disease Detection Using PPG Signals
Time Frame: June 2024 - September 2024
|
The primary outcome measure of this study is to evaluate the diagnostic accuracy of an AI model in detecting venous disease through the using PPG signals.
This will be quantified by assessing the sensitivity and specificity of the AI model when analysing PPG signals from healthy participants without venous diease, and non-healthy participants with venous disease, without the need for direct intervention of a vascular consultant.
These results will help evaluate the AI model in terms of how accurately it can identify Venous disease.
|
June 2024 - September 2024
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Investigators
- Principal Investigator: Mark Whiteley, The Whiteley Clinic
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Estimated)
June 1, 2024
Primary Completion (Estimated)
July 1, 2024
Study Completion (Estimated)
September 1, 2024
Study Registration Dates
First Submitted
May 22, 2024
First Submitted That Met QC Criteria
May 28, 2024
First Posted (Actual)
May 29, 2024
Study Record Updates
Last Update Posted (Actual)
May 31, 2024
Last Update Submitted That Met QC Criteria
May 29, 2024
Last Verified
May 1, 2024
More Information
Terms related to this study
Other Study ID Numbers
- TWC-SD-2024-05
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
NO
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
Yes
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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