mlsanityData to 14 Oct 2026

SSSD-ECG-nle: New Label Embeddings with Structured State-Space Models for ECG generation

arXiv 2407.11108 ↗First posted 15 Jul 2024eess.SP cs.LGcited by 1

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

An electrocardiogram (ECG) is vital for identifying cardiac diseases, offering crucial insights for diagnosing heart conditions and informing potentially life-saving treatments. However, like other types of medical data, ECGs are subject to privacy concerns when distributed and analyzed. Diffusion models have made significant progress in recent years, creating the possibility for synthesizing data comparable to the real one and allowing their widespread adoption without privacy concerns. In this paper, we use diffusion models with structured state spaces for generating digital 10-second 12-lead ECG signals. We propose the SSSD-ECG-nle architecture based on SSSD-ECG with a modified conditioning mechanism and demonstrate its efficiency on downstream tasks. We conduct quantitative and qualitative evaluations, including analyzing convergence speed, the impact of adding positive samples, and assessment with physicians' expert knowledge. Finally, we share the results of physician evaluations and also make synthetic data available to ensure the reproducibility of the experiments described.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 26 of its 40 references that are in the map. First posted on arXiv 15 Jul 2024.

Builds on

26 of 40 references.

Closest ancestors · 2

Same direction, newest first

  1. 2023DiffECG: A Versatile Probabilistic Diffusion Model for ECG Signals Synthesis2 Jun
  2. 2023Synthetic ECG Signal Generation using Probabilistic Diffusion Models4 Mar

Other references · 24

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  3. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
  4. 2022Classifier-Free Diffusion Guidancecited by 5,847
  5. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,101
  6. 2016Improved Techniques for Training GANscited by 2,970
  7. 2021Efficiently Modeling Long Sequences with Structured State Spacescited by 2,465
  8. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,114
  9. 2022On Distillation of Guided Diffusion Modelscited by 725
  10. 2021Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layerscited by 608
  11. 2020HiPPO: Recurrent Memory with Optimal Polynomial Projectionscited by 605
  12. 2018Bag of Tricks for Image Classification with Convolutional Neural Networkscited by 431
12 more
  1. 2022Diffusion-based Time Series Imputation and Forecasting with Structured State Space Modelscited by 198
  2. 2021Federated Learning for Smart Healthcare: A Surveycited by 184
  3. 2019Automatic diagnosis of the 12-lead ECG using a deep neural networkcited by 164
  4. 2018Bias and Generalization in Deep Generative Models: An Empirical Studycited by 83
  5. 2019Differential Privacy-enabled Federated Learning for Sensitive Health Datacited by 44
  6. 2022A Multifaceted Benchmarking of Synthetic Electronic Health Record Generation Modelscited by 43
  7. 2023Diffusion-based Conditional ECG Generation with Structured State Space Modelscited by 36
  8. 2020SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classificationcited by 32
  9. 2023TSGBench: Time Series Generation Benchmarkcited by 26
  10. 2023Accelerating Guided Diffusion Sampling with Splitting Numerical Methodscited by 13
  11. 2023Deep Generative Models for Physiological Signals: A Systematic Literature Reviewcited by 7
  12. 2023Deep Neural Networks Generalization and Fine-Tuning for 12-lead ECG Classificationcited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026ECG-RSI: Recursive Self-Improvement through Targeted Electrocardiogram Waveform Evolutioncited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025High-Fidelity Synthetic ECG Generation via Mel-Spectrogram Informed Diffusion Training
  2. 2025Simulator and Experience Enhanced Diffusion Model for Comprehensive ECG Generation
  3. 2025Generating Realistic Multi-Beat ECG Signals
  4. 2022Advancing the State-of-the-Art for ECG Analysis through Structured State Space Models
  5. 2025ECGTwin: Personalized ECG Generation Using Controllable Diffusion Model
  6. 2023Towards quantitative precision for ECG analysis: Leveraging state space models, self-supervision and patient metadata
  7. 2025ECG-aBcDe: Overcoming Model Dependence, Encoding ECG into a Universal Language for Any LLM
  8. 2026Pretraining Strategies and Scaling for ECG Foundation Models: A Systematic Study