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--- |
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license: bsd |
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language: |
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- en |
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tags: |
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- ECG |
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- Synthetic ECG |
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pipeline_tag: unconditional-image-generation |
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--- |
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# deepfake-ecg |
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[Paper](https://www.nature.com/articles/s41598-021-01295-2) |
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[GitHub](https://github.com/vlbthambawita/deepfake-ecg) |
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[Pre-generated ECGs (150k)](https://osf.io/6hved/) |
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--- |
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# To generate synthetic ECGs from Hugging face |
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```python |
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from transformers import AutoModel |
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model = AutoModel.from_pretrained("deepsynthbody/deepfake_ecg", trust_remote_code=True) |
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out = model(num_samples=5) |
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``` |
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## [Pulse2Pulse - development repo](https://github.com/vlbthambawita/Pulse2Pulse) |
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If you want to train the model from scratch, please refere our development repository Pulse2Pulse. |
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--- |
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## Usage |
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The generator functions can generate DeepFake ECGs with 8-lead values [lead names from first coloum to eighth colum: **'I','II','V1','V2','V3','V4','V5','V6'**] for 10s (5000 values per lead). These 8-leads format can be converted to 12-leads format using the following equations. |
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``` |
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lead III value = (lead II value) - (lead I value) |
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lead aVR value = -0.5*(lead I value + lead II value) |
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lead aVL value = lead I value - 0.5 * lead II value |
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lead aVF value = lead II value - 0.5 * lead I value |
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``` |
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### Pre-generated DeepFake ECGs and corresponding MUSE reports are here: https://osf.io/6hved/ or (https://huggingface.co/datasets/deepsynthbody/deepfake_ecg) |
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- In this repository, there are two DeepFake datasets: |
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1. 150k dataset - Randomly generated 150k DeepFakeECGs |
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2. Filtered all normals dataset - Only "Normal" ECGs filtered using the MUSE analysis report |
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## A real ECG vs a DeepFake ECG (from left to right): |
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## A sample DeepFake ECG: |
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## Contributing |
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Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. |
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Please make sure to update tests as appropriate. |
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## Citation: |
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```latex |
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@article{thambawita2021deepfake, |
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title={DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine}, |
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author={Thambawita, Vajira and Isaksen, Jonas L and Hicks, Steven A and Ghouse, Jonas and Ahlberg, Gustav and Linneberg, Allan and Grarup, Niels and Ellervik, Christina and Olesen, Morten Salling and Hansen, Torben and others}, |
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journal={Scientific reports}, |
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volume={11}, |
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number={1}, |
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pages={1--8}, |
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year={2021}, |
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publisher={Nature Publishing Group} |
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} |
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``` |
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## License |
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[MIT](https://choosealicense.com/licenses/mit/) |
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## For more details: |
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Please contact: vajira@simula.no, michael@simula.no |
