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license: mit
library_name: pytorch
tags:
- sensor-time-series
- physiological-signal
- generative-model
- flow-matching
language:
- en
datasets:
- physionet/mimic-iv-ecg
---
# SensorGen
[](#)
[](#)
[](https://github.com/yang-ai-lab/SensorGen)
[](https://huggingface.co/yang-ai-lab/SensorGen-SiT)
[](https://www.python.org/)
[](https://pytorch.org/)
This repository hosts the pre-trained checkpoints used in the SensorGen study
("*Signal or Noise? Understanding Generative Models for Real-World Sensor
Time Series*").
| Checkpoint | Task | Dataset |
|------------|------|---------|
| `text2ecg.pt` | Text-to-ECG | MIMIC-IV ECG |
| `bp_translation.pt` | PPG and NIBP to invasive BP | VitalDB |
## Usage
Pair this checkpoint repository with the GitHub code release at
**[yang-ai-lab/SensorGen](https://github.com/yang-ai-lab/SensorGen)**.
### Download a single checkpoint
```python
from huggingface_hub import hf_hub_download
ckpt_path = hf_hub_download(
repo_id="yang-ai-lab/SensorGen",
filename="text2ecg.pt",
)
```
### Download all checkpoints
```bash
hf download yang-ai-lab/SensorGen --local-dir ./ckpts
```
## Task specifications
| Task | Target `x` | C × T | `c_1` (sparse) | `c_2` (dense) |
|------|------------|-------|----------------|---------------|
| Text-to-ECG | 12-lead ECG, 10 s @ 100 Hz | 12 × 1,000 | Free-text ECG report (CLIP-encoded) | — |
| PPG → invasive BP | Arterial blood pressure, 30 s @ 50 Hz | 1 × 1,500 | 6-D non-invasive BP statistics | PPG waveform, 1 × 1,500 |
## Datasets
Neither MIMIC-IV ECG nor VitalDB are redistributed in this repository.
Credentialed access is required from the original data providers:
- **MIMIC-IV ECG** — [PhysioNet credentialed access](https://physionet.org/content/mimic-iv-ecg/)
- **VitalDB** — [vitaldb.net](https://vitaldb.net)
Preprocessing pipelines that convert the raw releases into the HDF5
layout consumed by these checkpoints are documented in the GitHub README.
## Limitations and responsible use
- The generated waveforms reflect statistical patterns in the training corpus and **must not be used for clinical
diagnosis or as a substitute for real patient recordings**.
- These models are released for *research use*. They are not approved
medical devices and have not been evaluated for clinical safety or
efficacy.
## Citation
If you use any of these checkpoints, please cite the SensorGen paper:
```bibtex
@article{shuai2026sensorgen,
title={Signal or Noise? Understanding Generative Models for Real-World Sensor Time Series},
author={Shuai, Zitao and Xu, Zongzhe and Wu, Yuntian and Li, Sirui and Li, Tianhong and Yang, Yuzhe},
journal={arXiv preprint arXiv:2607.04245},
year={2026}
}
```
## License
This release is distributed under the MIT License. |