DELTA (Detecting and Predicting Atrial Fibrillation in Post-Stroke Patients) (NCT05795842)
Develop and Validate Machine-Learning Algorithm to Detect Atrial Fibrillation With Wearable Devices
🩺 Plain-English Summary (8th-Grade Level)
Atrial Fibrillation (AF) is an abnormal heart rhythm. Because AF is often asymptomatic, it often remains undiagnosed in the early stages. Anticoagulant therapy greatly reduces the risks of stroke in patients diagnosed with AF. However, diagnosis of AF requires long-term ambulatory monitoring procedures that are burdensome and/or expensive. Smart devices (such as Apple or Fitbit) use light sensors (called "photoplethysmography" or PPG) and motion sensors (called "accelerometers") to continuously record biometric data, including heart rhythm. Smart devices are already widely adopted. This study seeks to validate an investigational machine-learning software (also called "algorithms") for the long-term monitoring and detection of abnormal cardiac rhythms using biometric data collected from consumer smart devices. The research team aims to enroll 500 subjects who are being followed after a stroke event of uncertain cause at the Emory Stroke Center. Subjects will undergo standard long-term cardiac monitoring (ECG), using FDA-approved wearable devices fitted with skin electrodes or implantable continuous recorders, and backed by FDA-approved software for abnormal rhythm detection. Patients will wear a study-provided consumer wrist device at home, for the 30 days of ECG monitoring, 23 hours a day. At the end of the 30 days, the device data will be uploaded to a secure cloud server and will be analyzed offline using proprietary software (called "algorithms") and artificial intelligence strategies. Detection of AF events using the investigational algorithms will be compared to the results from the standard monitoring to assess their reliability. Attention will be paid to recorded motion artifacts that can affect the quality and reliability of recorded signals. The ultimate aim is to establish that smart devices can potentially be used for monitoring purposes when used with specialized algorithms. Smart devices could offer an affordable alternative to standard-of-care cardiac monitoring.
Who can join: Review the eligibility criteria below.
Location: Emory Clinic — Atlanta, Georgia
Age range: 55 Years
🧪 Interventions in This Study
📋 "Do I Qualify?" — 1-Minute Self Screener
Instant ChecklistFull eligibility criteria are available on the official NIH protocol. View the criteria ↗
📍 All Participating Trial Locations (1 Sites)
- Emory Clinic — Atlanta, Georgia
📞 Contact the Study Coordinator
Phone: (404) 712-8520
Email: xhu40@emory.edu
Coordinator details come directly from the registered NIH protocol. Confirm the study is still recruiting before traveling.
💰 Cost, Insurance & Patient Rights
- 100% Free Items: The investigational treatment and protocol-required procedures are supplied at zero cost by the sponsor.
- Routine Patient Care: Under federal law (ACA § 2709) and many state statutes, routine care costs are covered during participation.
- Voluntary Participation: You may withdraw at any time without affecting your standard medical care.
More studies in Stroke, Ischemic
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- Visual Rehabilitation After Occipital Stroke — Rochester, New York
- Pathophysiology and Risk of Atrial Fibrillation Detected After Ischemic Stroke — London, Ontario
- The REACTplusNMES Trial: A Double-blinded RCT — Chicago, Illinois
- Transitional Care Program to Improve Risk Factors in Stroke Survivors — Winchester, Virginia
Explore by condition: All Stroke, Ischemic clinical trials
💡 How to Participate
- Check the checklist above to see if you may qualify.
- Contact the study coordinator using the phone/email above.
- Ask about the visit schedule, what is covered at no cost, and any travel support.
- Confirm with your own doctor before making a decision.