Trials / Unknown
UnknownNCT05802563
Machine Learning Enabled Time Series Analysis in Medicine
Pattern Recognition in Heart Rate Variability Using Fitness Trackers in Cardiovascular Disease
- Status
- Unknown
- Phase
- —
- Study type
- Observational
- Enrollment
- 200 (estimated)
- Sponsor
- HagaZiekenhuis · Academic / Other
- Sex
- All
- Age
- 18 Years – 85 Years
- Healthy volunteers
- Accepted
Summary
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.
Conditions
Interventions
| Type | Name | Description |
|---|---|---|
| DEVICE | fitness tracker | Study subjects will wear a Fitbit fitness tracker |
Timeline
- Start date
- 2022-05-24
- Primary completion
- 2023-09-01
- Completion
- 2023-09-01
- First posted
- 2023-04-06
- Last updated
- 2023-04-07
Locations
1 site across 1 country: Netherlands
Source: ClinicalTrials.gov record NCT05802563. Inclusion in this directory is not an endorsement.