12 Leads ECG is essential for examining cardio status. However, most commercial-grade products are unable to capture full 12 Leads ECG signal. And so, Reconstructed 12 Leads ECG Signal might be a better solution for identifying arrhythmia for data collected by smart devices. Here I bulid a Deep Learning model with U-Net Architecture for this specific task.
Here are reconstructed ECG charts of this model.
Chart of Losses on each epochs
I built this model with Code-15% dataset. You can find the description and original data from following link. https://zenodo.org/record/4916206
You can also download cleaned data for this particular project via following Link: https://1drv.ms/u/s!ArQCikHAsFj6oPJoQY7h9rIggjoaug?e=YjNprR
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Learning to See in the Dark: https://arxiv.org/abs/1805.01934
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I am sorry that I lost the original source of my U-Net Implementation. Please let me know if you are the author.