Clinical trial NCT06433024: Training of a Artificial Intelligence Model to Detect Venous Diseases Using PPG Technology
Official title: A Pilot Study Using AI Algorithms and PPG Technology for the Detection of Venous Diseases
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Venous Disease
Lead sponsor: The Whiteley Clinic
Sponsor class: OTHER
First posted: 2024-05-29
Enrollment: 20
Sex: ALL
Minimum age (years): 18
Maximum age (years): 80
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: PROSPECTIVE
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.

Brief summary: 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.


Eligibility criteria: 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.

Primary outcomes:
measure: Diagnostic Accuracy of an AI Model for Venous Disease Detection Using PPG Signals
timeFrame: June 2024 - September 2024
Secondary outcomes:
Other outcomes:
Locations:
city: Guildford
country: United Kingdom
facility: The Whiteley Clinic
Study officials:
affiliation: The Whiteley Clinic
name: Mark Whiteley
role: PRINCIPAL_INVESTIGATOR
References: