Personalized Blood Pressure Care Using IoMTs and Artificial Intelligence

NCT ID: NCT04543656

Last Updated: 2021-09-28

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

100 participants

Study Classification

INTERVENTIONAL

Study Start Date

2020-10-01

Study Completion Date

2022-06-30

Brief Summary

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In this RCT, up to 100 adults classified as pre-hypertensive will be randomized to either an artificial intelligence (AI) based lifestyle intervention group or an active control group with a 1 to 1 ratio. Both groups will receive an identical activity tracker (Samsung Galaxy Watch) and BP monitor (Omron Evolv). The AI intervention group will receive automated and personalized lifestyle recommendations based on their lifestyle (e.g. sleep, exercise and diet) and blood pressure (BP) data, involving an automated analytics engine using statistics and machine learning. The active control group will not receive these lifestyle recommendations. The investigators aim to assess objectively the effectiveness of the AI-based personalized lifestyle recommendations on the patients BP.

Detailed Description

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Conditions

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Pre-hypertension

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

PREVENTION

Blinding Strategy

SINGLE

Participants

Study Groups

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AI-Based Lifestyle Recommendations Group

Participants in this group receive AI-based, personalized lifestyle recommendations based on analysis of their activity tracker and blood pressure data.

Group Type EXPERIMENTAL

AI-Based Lifestyle Recommendations

Intervention Type BEHAVIORAL

The intervention provides participants with automated and personalized lifestyle recommendations involving a sophisticated analytics engine using advanced statistics and machine learning.

Control Group

Participants in this group do not receive the lifestyle recommendations, but are provided with an identical activity tracker and blood pressure monitor.

Group Type ACTIVE_COMPARATOR

No Lifestyle Recommendations

Intervention Type OTHER

The control group receives an identical activity tracker and BP monitor in order to objectively assess the effectiveness of the experimental group intervention.

Interventions

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AI-Based Lifestyle Recommendations

The intervention provides participants with automated and personalized lifestyle recommendations involving a sophisticated analytics engine using advanced statistics and machine learning.

Intervention Type BEHAVIORAL

No Lifestyle Recommendations

The control group receives an identical activity tracker and BP monitor in order to objectively assess the effectiveness of the experimental group intervention.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* age ≥18 years
* SBP between 130 mmHg to 139 mmHg or/and DBP between 80 to 89 mmHg in a research office
* speaking and reading English
* having an iPhone 8 or newer or an Android x or newer

Exclusion Criteria

* currently taking antihypertensive medication
* self-reported diagnosis of coronary heart disease, medical condition or other physical problem necessitating special attention in an exercise program (e.g., cancer, eating disorder, uncontrolled diabetes)
* current participation in a lifestyle modification program or research study
* self-report of being currently pregnant
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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University of California, San Diego

OTHER

Sponsor Role lead

Responsible Party

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Sujit Dey

Principal Investigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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University of California, San Diego

La Jolla, California, United States

Site Status RECRUITING

Countries

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United States

Central Contacts

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Sujit Dey, PhD

Role: CONTACT

8587617518

Facility Contacts

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Sujit Dey

Role: primary

Related Links

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https://ieeexplore.ieee.org/abstract/document/8822927

Offline and Online Learning Techniques for Personalized Blood Pressure Prediction and Health Behavior Recommendations

Other Identifiers

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1

Identifier Type: -

Identifier Source: org_study_id

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