mlsanityData to 7 Oct 2026

Deep Generative Models for Physiological Signals: A Systematic Literature Review

arXiv 2307.06162 ↗First posted 12 Jul 2023cs.LG cs.AI eess.SPcited by 7

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Abstract (arXiv)

In this paper, we present a systematic literature review on deep generative models for physiological signals, particularly electrocardiogram (ECG), electroencephalogram (EEG), photoplethysmogram (PPG) and electromyogram (EMG). Compared to the existing review papers, we present the first review that summarizes the recent state-of-the-art deep generative models. By analyzing the state-of-the-art research related to deep generative models along with their main applications and challenges, this review contributes to the overall understanding of these models applied to physiological signals. Additionally, by highlighting the employed evaluation protocol and the most used physiological databases, this review facilitates the assessment and benchmarking of deep generative models.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 28 of its 105 references that are in the map. First posted on arXiv 12 Jul 2023.

Builds on

28 of 105 references.

References · 28

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  3. 2022Diffusion Models for Medical Image Analysis: A Comprehensive Surveycited by 269
  4. 2022Diffusion-based Time Series Imputation and Forecasting with Structured State Space Modelscited by 195
  5. 2023Diffusion-based Conditional ECG Generation with Structured State Space Modelscited by 35
  6. 2020CardioGAN: Attentive Generative Adversarial Network with Dual Discriminators for Synthesis of ECG from PPGcited by 34
  7. 2020SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classificationcited by 32
  8. 2019Deep Learning in Alzheimer's disease: Diagnostic Classification and Prognostic Prediction using Neuroimaging Datacited by 30
  9. 2022DeScoD-ECG: Deep Score-Based Diffusion Model for ECG Baseline Wander and Noise Removalcited by 25
  10. 2023Synthetic ECG Signal Generation using Probabilistic Diffusion Modelscited by 22
  11. 2022EEG2Vec: Learning Affective EEG Representations via Variational Autoencoderscited by 14
  12. 2018Deep Generative Models in the Real-World: An Open Challenge from Medical Imagingcited by 12
16 more
  1. 2022Applications of Generative Adversarial Networks in Neuroimaging and Clinical Neurosciencecited by 11
  2. 2021An Accurate Non-accelerometer-based PPG Motion Artifact Removal Technique using CycleGANcited by 10
  3. 2023DiffECG: A Versatile Probabilistic Diffusion Model for ECG Signals Synthesiscited by 9
  4. 2020Electrocardiogram Generation and Feature Extraction Using a Variational Autoencodercited by 8
  5. 2020EEG to fMRI Synthesis: Is Deep Learning a candidate?cited by 8
  6. 2021ECG-Adv-GAN: Detecting ECG Adversarial Examples with Conditional Generative Adversarial Networkscited by 8
  7. 2023EEG Synthetic Data Generation Using Probabilistic Diffusion Modelscited by 8
  8. 2021Conditional Generation of Periodic Signals with Fourier-Based Decodercited by 6
  9. 2022Arrhythmia Classification using CGAN-augmented ECG Signalscited by 6
  10. 2022Leveraging Statistical Shape Priors in GAN-based ECG Synthesiscited by 4
  11. 2019Visual Evaluation of Generative Adversarial Networks for Time Series Datacited by 2
  12. 2023ECGAN: Self-supervised generative adversarial network for electrocardiographycited by 2
  13. 2018Learning disentangled representation from 12-lead electrograms: application in localizing the origin of Ventricular Tachycardiacited by 1
  14. 2018Deep Generative Model with Beta Bernoulli Process for Modeling and Learning Confounding Factorscited by 1
  15. 2022Evolving SimGANs to Improve Abnormal Electrocardiogram Classificationcited by 1
  16. 2022Out-of-Distribution Detection using BiGAN and MDLcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 3; 2026: 2.

7 papers.

  1. 2024Entropy-Informed Weighting Channel Normalizing Flow for Deep Generative Modelscited by 5
  2. 2025From Prototypes to Sparse ECG Explanations: SHAP-Driven Counterfactuals for Multivariate Time-Series Multi-class Classificationcited by 3
  3. 2026EMGFlow: Robust and Efficient Surface Electromyography Synthesis via Flow Matchingcited by 1
  4. 2024SSSD-ECG-nle: New Label Embeddings with Structured State-Space Models for ECG generationcited by 0
  5. 2025Imputation of Missing Data in Smooth Pursuit Eye Movements Using a Self-Attention-based Deep Learning Approachcited by 0
  6. 2025Enhancing Fatigue Detection through Heterogeneous Multi-Source Data Integration and Cross-Domain Modality Imputationcited by 0
  7. 2026Physiological World Models for Human State Transitionscited by 0