Machine Learning Enabled Time Series Analysis in Medicine (ME-TIME)

April 6, 2023 updated by: Ivo van der Bilt, HagaZiekenhuis

Pattern Recognition in Heart Rate Variability Using Fitness Trackers in Cardiovascular Disease

The goal of this observational cohort study is to investigate the potential of fitness trackers in combination with machine learning algorithms to identify cardiovascular disease specific patterns.

Two hundred participants will be enrolled:

  1. 50 with heart failure
  2. 50 with atrial fibrillation
  3. 100 (healthy) individuals without the former two conditions

All participants are given a Fitbit device and monitored for three months. Researchers will compare differences in heart rate variability patterns between the groups and devise a machine learning algorithm to detect these patterns automatically.

Study Overview

Status

Enrolling by invitation

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Anticipated)

200

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Netherlands
    • Zuid-Holland
      • Den Haag, Zuid-Holland, Netherlands, 2545 AA
        • HagaZiekenhuis

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 85 years (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

All included participants will receive an electrocardiogram.

Description

Inclusion Criteria:

  • systolic heart failure (LVEF < 35%)
  • Atrial fibrillation without heart failure
  • Individuals without cardiovascular disease

Exclusion Criteria:

  • > 85 years old
  • Recent pulmonary venous antrum isolation procedure (<1 year)
  • (end stage) kidney failure
  • (end stage) liver failure
  • Study participants with known systemic active inflammatory disease
  • Study participants with impaired mental state
  • Inability to use a fitness tracker or mobile phone
  • Impaired cognition and inability to understand the study protocol

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Heart Failure
Study participants with systolic heart failure (Left ventricular ejection fraction < 35%) without documented atrial fibrillation
Device: fitness tracker
Study subjects will wear a Fitbit fitness tracker
Other Names:
  • Fitbit Charge 5, Fitbit Inspire 2
Atrial Fibrillation
Study participants with documented atrial fibrillation without heart failure
Device: fitness tracker
Study subjects will wear a Fitbit fitness tracker
Other Names:
  • Fitbit Charge 5, Fitbit Inspire 2
Reference
Individuals without cardiovascular disease
Device: fitness tracker
Study subjects will wear a Fitbit fitness tracker
Other Names:
  • Fitbit Charge 5, Fitbit Inspire 2

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Cardiovascular disease detection with an AI algorithm
Time Frame: Three months
adequate sensitivity/specificity in an algorithm to detect atrial fibrillation and heart failure
Three months

Secondary Outcome Measures

Outcome Measure
Time Frame
Detection of absence of cardiovascular disease
Time Frame: Three months
Three months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

HagaZiekenhuis

Collaborators

Delft University of Technology

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

May 24, 2022

Primary Completion (Anticipated)

September 1, 2023

Study Completion (Anticipated)

September 1, 2023

Study Registration Dates

First Submitted

March 27, 2023

First Submitted That Met QC Criteria

March 27, 2023

First Posted (Actual)

April 6, 2023

Study Record Updates

Last Update Posted (Actual)

April 7, 2023

Last Update Submitted That Met QC Criteria

April 6, 2023

Last Verified

April 1, 2023

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • metime

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

We are planning to release the full data set in the future.

IPD Sharing Time Frame

Expected release in 2026

IPD Sharing Access Criteria

  • Research institute
  • Open Access (full disclosure of results)
  • Clear data analysis plan

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • ANALYTIC_CODE

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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