---
pretty_name: "DREAMT: Dataset for Real-time sleep stage Estimation using Multisensor wearable Technology"
tags:
- timeseries
- health
- sleep-staging
- wearables
- physionet
- medical
license: "other"
task_categories:
- other
---

## Dataset Description

**DREAMT** (Dataset for Real-time sleep stage EstimAtion using Multisensor wearable Technology) is a dataset designed to facilitate the development and evaluation of machine learning models for sleep stage estimation using data from multisensor wearable devices. 

- **Version:** 2.1.0
- **Repository:** [PhysioNet: DREAMT v2.1.0](https://physionet.org/content/dreamt/2.1.0/)

## Access Policy & Licensing

Due to the sensitive nature of health data, this dataset is restricted and cannot be downloaded directly without authorization. 

* **Access Policy:** Only registered PhysioNet users who sign the specified Data Use Agreement (DUA) can access the data files.
* **License:** PhysioNet Restricted Health Data License 1.5.0
* **Data Use Agreement:** PhysioNet Restricted Health Data Use Agreement 1.5.0

Before accessing the data, please visit the [dataset page on PhysioNet](https://physionet.org/content/dreamt/2.1.0/) and follow the instructions to sign the DUA.

## Citation Information

If you use this dataset in your research, you **must** include the following citations.

**1. Cite the dataset resource:**
> Wang, K., Yang, J., Shetty, A., & Dunn, J. (2025). DREAMT: Dataset for Real-time sleep stage EstimAtion using Multisensor wearable Technology (version 2.1.0). PhysioNet. RRID:SCR_007345. https://doi.org/10.13026/7r9r-7r24

**2. Cite the original publication:**
> Will Ke Wang, Jiamu Yang, Leeor Hershkovich, Hayoung Jeong, Bill Chen, Karnika Singh, Ali R Roghanizad, Md Mobashir Hasan Shandhi, Andrew R Spector, Jessilyn Dunn. (2024). Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:380-396.

**3. Include the standard citation for PhysioNet:**
> Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215–e220. RRID:SCR_007345.