Accepted for/Published in: JMIR Cardio
Date Submitted: Oct 27, 2025
Open Peer Review Period: Nov 6, 2025 - Jan 1, 2026
Date Accepted: Sep 9, 2026
(closed for review but you can still tweet)
Generation of 12-Lead ECG Using Smartwatches in Patients with Cardiac Conditions: A Clinical Validation Study
ABSTRACT
Background:
While smartwatches have revolutionized personal health monitoring, their utility for comprehensive cardiac assessment remains limited by single-lead electrocardiogram (ECG) acquisition. This study introduces a novel software-based methodology to reconstruct a full 12-lead ECG from sequential smartwatch recordings, aiming for diagnostic comparability with conventional systems.
Objective:
We present a proof-of-concept clinical validation of this approach, addressing a critical unmet need in accessible cardiac diagnostics.
Methods:
A signal processing pipeline was developed to preserve ECG morphology across sequential smartwatch lead recordings, achieving synchronization via RR interval–based temporal resampling to generate a coherent 12-lead ECG. A clinical validation study was conducted in 20 patients with diverse cardiac pathologies and 2 healthy controls. Smartwatch-derived ECGs were compared with standard recordings. Diagnostic accuracy and visual interpretability were assessed by 85 healthcare professionals through a structured questionnaire. An independent arrhythmologist provided qualitative clinical validation for all cases.
Results:
The primary objective of reconstructing a 12-lead ECG from smartwatch signals was successfully achieved. Visual correlation scores between smartwatch-derived and conventional ECGs ranged from 77% to 91.4%, with a mean of 81%, indicating strong concordance. An average of 95.5% alignment in the electrical axis was observed. The highest diagnostic agreement was found in ischemic heart disease and bundle branch blocks, supporting clinical relevance.
Conclusions:
This study demonstrates proof-of-concept for reconstructing a 12-lead ECG from smartwatch-acquired signals with diagnostic comparability to conventional systems. This method expands smartwatch ECG capabilities, enabling accessible, advanced cardiovascular diagnostics and proactive patient monitoring. A European patent has been filed for this technology (reference:EP25382712.5).
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.