PaperarXiv:2605.12541

PG-LRF: Physiology-Guided Latent Rectified Flow for Electro-Hemodynamic PPG-to-ECG Generation

Venue listed2026Added Oct 25, 2026

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Authors: Xiaoda Wang, Minxiao Wang, Kaiqiao Han, Defu Cao, Ching Chang, Yidan Shi, Runze Yan, Xiao Luo, Yan Liu, Xiao Hu,

+3 moreYizhou Sun, Wei Wang, Carl Yang

NeurIPS 2026 (listed on Emory CS page)

TL;DR

PG-LRF introduces physiology-guided latent rectified flow for PPG-to-ECG generation on MC-MED. Simulator-regularized flow improves waveform fidelity and interval metrics over prior generative baselines and lifts a downstream CVD label probe on synthesized ECG.

  • arXiv 2605.12541
  • NeurIPS 2026 listing on Emory lab page
  • MC-MED waveform MAE 0.71 / HR MAE 3.94 bpm
  • Interval MAE (ms): PR 59.9, QRS 38.6, QT 29.3, QTcF 32.2
  • Generated-ECG CVD Macro-AUROC 0.633 vs PaPaGei-on-PPG 0.545

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Tasks & signals

Signals

Keywords

ppg-to-ecggenerativerectified-flowphysiology-guidedemoryneurips-2026

Models

How it works

How GPT-PPG works: Setup → Method → TargetSetup: PPG (Photoplethysmogram); ECG (Electrocardiogram). Method: GPT-PPG.SetupPPG: PhotoplethysmogramPPGPhotoplethysmogramECG: ElectrocardiogramECGElectrocardiogramMethodGPT-PPG

Cite this paper

APA

Wang, X., Wang, M., Han, K., Cao, D., Chang, C., Shi, Y., Yan, R., Luo, X., Liu, Y., Hu, X., Sun, Y., Wang, W., & Yang, C. (2026). PG-LRF: Physiology-Guided Latent Rectified Flow for Electro-Hemodynamic PPG-to-ECG Generation. NeurIPS 2026. https://arxiv.org/abs/2605.12541

BibTeX

@inproceedings{wang2026pglrf,
  title         = {{PG-LRF: Physiology-Guided Latent Rectified Flow for Electro-Hemodynamic PPG-to-ECG Generation}},
  author        = {Wang, Xiaoda and Wang, Minxiao and Han, Kaiqiao and Cao, Defu and Chang, Ching and Shi, Yidan and Yan, Runze and Luo, Xiao and Liu, Yan and Hu, Xiao and Sun, Yizhou and Wang, Wei and Yang, Carl},
  year          = {2026},
  booktitle     = {NeurIPS 2026},
  eprint        = {2605.12541},
  archivePrefix = {arXiv}
}

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