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CardioGAN: Attentive Generative Adversarial Network with Dual Discriminators for Synthesis of ECG from PPG
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| generate ECG from input PPG with CardioGAN | PPG heart-rate estimation · All datasets, 64-second window | MAE_HR: 9.74 -> 2.89 | Helped |
| generate ECG from input PPG with CardioGAN | PPG-to-ECG translation · BIDMC | MAE_HR: 2.3 -> 0.7 | Helped |
| generate ECG from input PPG with CardioGAN | PPG-to-ECG translation · CAPNO | MAE_HR: 1.2 -> 2.0 | Hurt |
| generate ECG from input PPG with CardioGAN | PPG-to-ECG translation · Dalia | MAE_HR: 11.1 -> 8.3 | Helped |
| generate ECG from input PPG with CardioGAN | PPG-to-ECG translation · WESAD | MAE_HR: 9.5 -> 8.6 | Helped |
| add a frequency-domain discriminator (ablation) | CardioGAN · All subjects, four datasets | MAE_HR: 9.57 -> 4.77 | Helped |
| add a frequency-domain discriminator (ablation) | CardioGAN · All subjects, four datasets | RMSE: 0.396 -> 0.364 | Helped |
| add generator attention (ablation) | CardioGAN · All subjects, four datasets | MAE_HR: 9.67 -> 4.77 | Helped |
| add generator attention (ablation) | CardioGAN · All subjects, four datasets | FD: 0.773 -> 0.694 | Helped |
| use paired rather than unpaired ECG-PPG training (ablation) | CardioGAN · All subjects, four datasets | RMSE: 0.364 -> 0.437 | Hurt |
| use paired rather than unpaired ECG-PPG training (ablation) | CardioGAN · All subjects, four datasets | MAE_HR: 4.77 -> 5.04 | Hurt |
Closest papers by meaning
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- Robustness and Visual Explanation for Black Box Image, Video, and ECG Signal Classification with Reinforcement Learning (AAAI 2024 · similarity 0.82)
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- Leveraging an ECG Beat Diffusion Model for Morphological Reconstruction from Indirect Signals (NeurIPS 2024 · similarity 0.82)
- Region-Disentangled Diffusion Model for High-Fidelity PPG-to-ECG Translation (AAAI 2024 · similarity 0.82)
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