A Photoplethysmography-Based Machine Learning Algorithm for Early Atrial Fibrillation Detection: A Prospective Validation Study

Recruiting Observational Study
Atrial Fibrillation (AF) Heart Failure
No Placebo Group Every participant receives an active treatment — no one gets a placebo. No Study Drug Researchers observe your health over time — no experimental treatment is given.
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At a Glance
Age
18 and older
Sex
Any
Study type
Observational
Participants needed
200 (estimated)
Sponsor
Seerlinq s. r. o. · Other
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About This Trial
This is a prospective study validating a new machine-learning algorithm that detects atrial fibrillation (AF) from photoplethysmography (PPG) signals, developed for integration into the Seerlinq remote monitoring platform. This algorithm builds on the same core PPG signal-processing technology as Seerlinq's HeartCore device, a CE-certified (Class IIb, MDR) device that monitors left ventricular fil…
Trial Locations
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Eligibility Criteria
Inclusion Criteria: * Adults ≥18 years with a diagnosis of heart failure (HFrEF, HFmrEF, or HFpEF) * 12-lead ECG performed to confirm cardiac rhythm classification (AF vs. non-AF) Exclusion Criteria: * Missing a valid PPG recording
Contacts

Marta Kollárová, MSc., PhD.

+421 950 896 026

marta.kollarova@premedix.org

CONTACT