Abstract
As the primary tool for monitoring cardiac health, a standard 12-lead ECG device is specialized medical equipment that is challenging to integrate into daily life. Meanwhile, existing portable ECG monitoring devices can only capture single-lead ECG, which is insufficient for health diagnosis. To address this issue, we propose a novel shifted diffusion model algorithm that utilizes a single-lead ECG to generate a standard 12-lead ECG. Our algorithm uses the detected single-lead ECG as the condition and employs the diffusion model to synthesize corresponding other 11-lead ECG. The extra shift is utilized in the forward process so that the model can learn better. Our approach has been tested on three datasets, yielding promising results.
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Acknowledgements
This work is supported by the National Natural Science Foundation of China (No. 62172018, No. 62102008) and Wuhan East Lake High-Tech Development Zone National Comprehensive Experimental Base for Governance of Intelligent Society.
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Liu, J., Li, H., Hong, S. (2024). Synthesis of Standard 12-Lead ECG from Single-Lead ECG Using Shifted Diffusion Models. In: Bifet, A., Krilavičius, T., Miliou, I., Nowaczyk, S. (eds) Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. ECML PKDD 2024. Lecture Notes in Computer Science(), vol 14949. Springer, Cham. https://doi.org/10.1007/978-3-031-70378-2_17
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