Ignite Creation Date:
2024-10-26 @ 3:39 PM
Last Modification Date:
2024-10-26 @ 3:39 PM
Study NCT ID:
NCT06577688
Status:
NOT_YET_RECRUITING
Last Update Posted:
None
First Post:
2024-08-27
Brief Title:
Smartphone Blood Pressure Measurement to Screen for Hypertension
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Assessing the Feasibility of Classifying People Using a Machine-learning Approached Based on Features Derived From Smartphone Video Data Recorded at the Persons Fingertip
Status:
NOT_YET_RECRUITING
Status Verified Date:
2024-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
Optiscreen
Brief Summary:
The goal of this observational study is to assess the feasibility of classifying people whose blood pressures are within hypertensive range using a machine-learning approach based on features derived from smartphone video data recorded at the patients fingertips The main questions it aims to answer are
Is a smartphone a reliable device for high blood pressure screening Is a smartphone a reliable device for blood pressure monitoring Participants will record their blood pressure with a smartphone at their fingertips and with an approved cuff device 3 times in the morning and 3 times in the evening for 7 days There will be two groups a volunteer presumed healthy and a volunteer addressed for a Home Blood pressure monitoring with the diagnosis of hypertension suspected
Researchers will compare the two groups to see if the smartphone can be reliable in terms of diagnosis and monitoring of the blood pressure comparing to a standard cuff device
Is a smartphone a reliable device for high blood pressure screening Is a smartphone a reliable device for blood pressure monitoring Participants will record their blood pressure with a smartphone at their fingertips and with an approved cuff device 3 times in the morning and 3 times in the evening for 7 days There will be two groups a volunteer presumed healthy and a volunteer addressed for a Home Blood pressure monitoring with the diagnosis of hypertension suspected
Researchers will compare the two groups to see if the smartphone can be reliable in terms of diagnosis and monitoring of the blood pressure comparing to a standard cuff device
Detailed Description:
This is a single-center observational pilot study Data will be collected prospectively on 100 participants maximum of 120 with ideally 50 presumed healthy volunteers and 50 participants with a suspected diagnosis of hypertension Presumably healthy volunteers will be recruited via flyers and participants presumed to be hypertensive will be recruited by the hypertension unit of the CHUV where they are referred for the search for a diagnosis of hypertension
To comply with the International Hypertension Societies guidelines for LMWH participants will measure their blood pressure for 7 consecutive days in the morning before taking medications and food and in the evening before dinner At each measurement time point participants will acquire three separate measurements one minute apart Participants will record signals by placing a fingertip of the right hand over a smartphone camera while simultaneously acquiring a baseline blood pressure measurement using a validated cuff device WatchBP O3 Ambulatory Microlife Widnau Switzerland on the left arm Please note that the smartphone and armband will be provided by the site investigator The data recorded using the smartphone will be processed and directly compared to the values obtained using the inflatable cuff device
In accordance with international guidelines for LMWH except those of the American Heart Association the threshold for hypertension is set at systolic blood pressure values 135 mmHg andor diastolic blood pressure values 85 mmHg
The aim of this study is to evaluate the feasibility of classifying people whose blood pressure is in the hypertensive range or not using a method based on machine learning To do this optical data will be recorded at the fingertip from a smartphone camera following the HBPM measurement protocol The optical signals will then be processed by a machine learning method to obtain the classification In other words we will attempt to evaluate the reliability of the machine learning method compared to the automatic oscillometric brachial cuff and therefore evaluate the feasibility of using the smartphone as a potential future tool for diagnosis screening and monitoring hypertension
The methods of screening diagnosis and monitoring of hypertensive pathologies are precise but require cumbersome equipment and are sometimes poorly available We hypothesize that smartphones can be used because of to their availability and their capacity to generate quality optical signals as a discriminating classifier in arterial hypertension thanks to the precision of a machine learning model hypothetically greater than a classification carried out by a random level
To comply with the International Hypertension Societies guidelines for LMWH participants will measure their blood pressure for 7 consecutive days in the morning before taking medications and food and in the evening before dinner At each measurement time point participants will acquire three separate measurements one minute apart Participants will record signals by placing a fingertip of the right hand over a smartphone camera while simultaneously acquiring a baseline blood pressure measurement using a validated cuff device WatchBP O3 Ambulatory Microlife Widnau Switzerland on the left arm Please note that the smartphone and armband will be provided by the site investigator The data recorded using the smartphone will be processed and directly compared to the values obtained using the inflatable cuff device
In accordance with international guidelines for LMWH except those of the American Heart Association the threshold for hypertension is set at systolic blood pressure values 135 mmHg andor diastolic blood pressure values 85 mmHg
The aim of this study is to evaluate the feasibility of classifying people whose blood pressure is in the hypertensive range or not using a method based on machine learning To do this optical data will be recorded at the fingertip from a smartphone camera following the HBPM measurement protocol The optical signals will then be processed by a machine learning method to obtain the classification In other words we will attempt to evaluate the reliability of the machine learning method compared to the automatic oscillometric brachial cuff and therefore evaluate the feasibility of using the smartphone as a potential future tool for diagnosis screening and monitoring hypertension
The methods of screening diagnosis and monitoring of hypertensive pathologies are precise but require cumbersome equipment and are sometimes poorly available We hypothesize that smartphones can be used because of to their availability and their capacity to generate quality optical signals as a discriminating classifier in arterial hypertension thanks to the precision of a machine learning model hypothetically greater than a classification carried out by a random level
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None