Data Collection and Evaluation of OptiBP Under Investigational Use
ConditionGeneral Population
Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorBiospectal
About this trial
The purpose of this study is to collect data to develop and evaluate the use of state-of-the-art machine learning approaches within a mobile phone application for the estimation of blood pressure.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Be at least 18 years old (at least 19 years old in Alabama and Nebraska, at least 21 years old in Puerto Rico);
Live in the United States of America
Have an Android smartphone
Have access to an arm-worn blood pressure monitor (cuff)
Disqualifiers
Known contact dermatitis to nickel/chromium
Lesion or deficiency on hand, preventing placing a finger on the smartphone camera
Known dysrhythmia like bigeminy, trigeminy, isolated VPB, atrial fibrillation
Trial design
Design model
Single group
Treatments tested in this trial
OptiBP Study app
DeviceEach participant will use OptiBP Study app to measure their blood pressure optically by applying their fingertip to their smartphone camera, and subsequently enter the blood pressure values obtained by measuring it with their own blood pressure cuff.
Treatment groups
500,000 Participants
are divided into 1 treatment groupGroup A: Principal ArmOther 1 intervention
Trial outcomes
Primary outcomes
1
Collect Blood Pressure (BP) data and assess performance of smartphone based BP estimations models
To collect data to train a machine-learning based solution for estimating blood pressure. Participants will simultaneously acquire blood pressure measurements through a cuff-based, automatic, over-the-counter blood pressure monitor at the upper arm, while recording an optical signal through the camera of a smartphone on the tip of the index of the opposite arm. The performance of the machine learning model will be assessed by calculating the mean and standard deviation of the error of blood pressure estimations versus cuff-based, automatic, over-the-counter blood pressure monitors.
Time frame
12 monthsSecondary outcomes
1
Safety by assessing inconvenience and adverse events
To identify potential use errors of an app that use the machine-learning model to estimate blood pressure. And to assess safety of the intervention.
Time frame
12 months Source ClinicalTrials.gov