mlsanityData to 7 Oct 2026

DiffECG: A Versatile Probabilistic Diffusion Model for ECG Signals Synthesis

arXiv 2306.01875 ↗First posted 2 Jun 2023cs.CV cs.LGcited by 9

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

Within cardiovascular disease detection using deep learning applied to ECG signals, the complexities of handling physiological signals have sparked growing interest in leveraging deep generative models for effective data augmentation. In this paper, we introduce a novel versatile approach based on denoising diffusion probabilistic models for ECG synthesis, addressing three scenarios: (i) heartbeat generation, (ii) partial signal imputation, and (iii) full heartbeat forecasting. Our approach presents the first generalized conditional approach for ECG synthesis, and our experimental results demonstrate its effectiveness for various ECG-related tasks. Moreover, we show that our approach outperforms other state-of-the-art ECG generative models and can enhance the performance of state-of-the-art classifiers.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 16 of its 37 references that are in the map. First posted on arXiv 2 Jun 2023.

Builds on

16 of 37 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023Synthetic ECG Signal Generation using Probabilistic Diffusion Models4 Mar

Other references · 15

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  4. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  5. 2020DiffWave: A Versatile Diffusion Model for Audio Synthesiscited by 1,339
  6. 2022Diffusion-based Time Series Imputation and Forecasting with Structured State Space Modelscited by 195
  7. 2019GP-VAE: Deep Probabilistic Time Series Imputationcited by 171
  8. 2022SAITS: Self-Attention-based Imputation for Time Seriescited by 167
  9. 2018An empirical study on evaluation metrics of generative adversarial networkscited by 81
  10. 2018ECG Heartbeat Classification: A Deep Transferable Representationcited by 76
  11. 2022Efficient Long Sequence Modeling via State Space Augmented Transformercited by 37
  12. 2023Diffusion-based Conditional ECG Generation with Structured State Space Modelscited by 35
3 more
  1. 2019Synthesis of Realistic ECG using Generative Adversarial Networkscited by 26
  2. 2022PulseImpute: A Novel Benchmark Task for Pulsative Physiological Signal Imputationcited by 9
  3. 2022Leveraging Statistical Shape Priors in GAN-based ECG Synthesiscited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 1; 2025: 6; 2026: 1.

9 papers.

  1. 2025Simulator and Experience Enhanced Diffusion Model for Comprehensive ECG Generationcited by 8
  2. 2023Deep Generative Models for Physiological Signals: A Systematic Literature Reviewcited by 7
  3. 2025FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generatorcited by 2
  4. 2025Generating Realistic Multi-Beat ECG Signalscited by 1
  5. 2024SSSD-ECG-nle: New Label Embeddings with Structured State-Space Models for ECG generationcited by 0
  6. 2025MM-DADM: Multimodal Drug-Aware Diffusion Model for Virtual Clinical Trialscited by 0
  7. 2025Approximately Equivariant Recurrent Generative Models for Quasi-Periodic Time Series with a Progressive Training Schemecited by 0
  8. 2025Imputation of Missing Data in Smooth Pursuit Eye Movements Using a Self-Attention-based Deep Learning Approachcited by 0
  9. 2026Signal or Noise? Understanding Generative Models for Real-World Sensor Time Seriescited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023Bayesian ECG reconstruction using denoising diffusion generative models
  2. 2023Improving Diffusion Models for ECG Imputation with an Augmented Template Prior
  3. 2025High-Fidelity Synthetic ECG Generation via Mel-Spectrogram Informed Diffusion Training
  4. 2025ECGTwin: Personalized ECG Generation Using Controllable Diffusion Model
  5. 2026ECG-WM: A Physiology-Informed ECG World Model for Clinical Intervention Simulation
  6. 2022DeScoD-ECG: Deep Score-Based Diffusion Model for ECG Baseline Wander and Noise Removal
  7. 2023Region-Disentangled Diffusion Model for High-Fidelity PPG-to-ECG Translation
  8. 2026DiSR-ECG: Residual Shifting Conditional Diffusion for Robust ECG Super-Resolution ↗