Personalized Blood Pressure Care Using IoMTs and Artificial Intelligence

Pre-hypertension Clinical Trial

Official title:

Personalized Blood Pressure Care for Prehypertensive Patients Using IoMTs and Artificial Intelligence

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04543656
• Other study ID #: 1
• Status: Recruiting
• Phase: N/A
• Start date: October 1, 2020
• Est. completion date: June 2022

Study information

• Verified date: September 2021
• Source: University of California, San Diego
• Contact: Sujit Dey, PhD
• Phone: 8587617518
• Email: dey[@]eng.ucsd.edu
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 100
• Est. completion date: June 2022
• Est. primary completion date: June 2022
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years and older

Eligibility

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

Related Conditions & MeSH terms

• Pre-hypertension
• Prehypertension

Intervention

Behavioral:
• 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.

Other:
• 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.

Locations

Country	Name	City	State
United States	University of California, San Diego	La Jolla	California

Sponsors (1)

Lead Sponsor	Collaborator
University of California, San Diego

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Average change in systolic blood pressure (SBP) in experimental vs. control group	Average SBP during the first and last week of a patient's enrollment will be used to calculate SBP change for each patient.	Initial 2 week data collection, weekly lifestyle recommendations, 6 months total
Primary	Average change in diastolic blood pressure (DBP) in experimental vs. control group	Average DBP during the first and last week of a patient's enrollment will be used to calculate DBP change for each patient.	Initial 2 week data collection, weekly lifestyle recommendations, 6 months total
Secondary	Number of patients in experimental group that followed lifestyle recommendations	This secondary outcome measure is interested in assessing patient engagement within the experimental group. Data from the activity tracker (steps, sleep quality, active minutes, etc.) will be used to assess whether a patient followed the lifestyle recommendations.	Initial 2 week data collection, weekly lifestyle recommendations, 6 months total

External Links

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