Published July 28, 2026 | Version v1
Dataset Open

RPT15 Demonstration Subset: Five-Subject Single-Lead ECG with R-, P-, and T-Peak Annotations at Multiple Sampling Rates

Authors/Creators

  • 1. EDMO icon University of California, San Diego

Contributors

  • 1. EDMO icon University of California, San Diego
  • 2. ROR icon San Diego State University

Description

RPT15 Demonstration Subset:

This record contains a five-subject demonstration subset of RPT15. It provides 300 seconds of single-lead ECG data per subject with manual R-, P-, and T-peak annotations.

The subset accompanies the manuscript “CardioAnnotate: An Interactive Toolkit for ECG Signal Processing, Annotation, Gaussian Process Correction, and Interoperable Data Exchange” and provides runnable example data under a permanent DOI. It is not the complete RPT15 dataset release.

The complete 42-subject archive is currently under review at PhysioNet. A link to the full release will be added to this record after publication.

Data contents

Each subject is provided at its native sampling rate and at fixed sampling rates of 250 Hz and 512 Hz. Every record contains one canonical ECG lead.

Data are distributed in:

  • NPZ format, including the ECG signal and metadata.

  • WFDB format, including a time-ordered annotation stream using N for R peaks, p for P peaks, and t for T peaks.

  • CSV and JSON provenance files identifying the source record, database, lead, native sampling rate, and extracted window.

  • A SHA256SUMS file containing checksums for the distributed files.

Record names follow the convention {subject_id}_{release}. Subject identifiers are preserved from the complete RPT15 archive and are therefore not contiguous. For example, 0001_variable in this subset and 0001_variable in the complete archive identify the same subject.

See README.md for the complete directory structure, metadata description, subject table, reconstruction instructions, and annotation-adjustment parameters.

License and attribution

The ECG signals are derived from PhysioNet databases made available under the Open Data Commons Attribution License v1.0. This demonstration subset is redistributed under the same license.

See LICENSE.txt for the applicable license terms and ATTRIBUTION.md for the source databases, source links, attribution notices, and required PhysioNet citation.

Citation

When using this demonstration subset, please cite:

Mojtahed H. RPT15 Sample: a 5-subject demonstration subset of single-lead ECG with R, P, and T peak annotations at various sampling rates [Dataset]. Zenodo, 2026. https://doi.org/10.5281/zenodo.21652810

Mojtahed H. CardioAnnotate: Browser-Based ECG Annotation, RR Correction, HRV Analysis, and Export [Computer software]. Zenodo, 2026. https://doi.org/10.5281/zenodo.20820831

Please also cite the source databases identified in ATTRIBUTION.md.

This subset was produced with CardioAnnotate. The publication reference for the accompanying manuscript will be added when it becomes available.

Related resources

CardioAnnotate toolkit live website: Launch CardioAnnotate

Project website: Visit the project website

Files

RPT15_demonstration_dataset.zip

Files (6.2 MB)

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Additional details

Related works

Is compiled by
Software: 10.5281/zenodo.20820831 (DOI)
Software: https://cardioannotate.github.io/ (URL)
Is part of
Other: https://mojtahed-ecglab.github.io/ (URL)

References

  • Mojtahed H. CardioAnnotate: Browser-Based ECG Annotation, RR Correction, HRV Analysis, and Export [Computer software]. Zenodo, 2026. https://doi.org/10.5281/zenodo.20820831
  • Pollard T, Moody BE, Lehman L, Gow B, Fernandes C, Xie C, Johnson A, Mark RG, Heldt T. PhysioNet as a global platform for biomedical research. Nature Health. 2026. https://doi.org/10.1038/s44360-026-00096-z
  • Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE. PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation. 2000;101(23):e215–e220.
  • Moody GB, Mark RG. The impact of the MIT-BIH Arrhythmia Database. IEEE Engineering in Medicine and Biology Magazine. 2001;20(3):45–50. PMID: 11446209.
  • Greenwald SD. Improved detection and classification of arrhythmias in noise-corrupted electrocardiograms using contextual information. PhD thesis, Harvard–MIT Division of Health Sciences and Technology, 1990.
  • Greenwald SD. Development and analysis of a ventricular fibrillation detector. MS thesis, MIT Department of Electrical Engineering and Computer Science, 1986.
  • Taddei A, Distante G, Emdin M, Pisani P, Moody GB, Zeelenberg C, Marchesi C. The European ST-T Database: standard for evaluating systems for the analysis of ST-T changes in ambulatory electrocardiography. European Heart Journal. 1992;13(9):1164–1172.
  • MIT-BIH Normal Sinus Rhythm Database. PhysioNet. https://physionet.org/content/nsrdb/1.0.0/