<b>Resting ECG Segmentation Dataset</b>

<b>Resting ECG Segmentation Dataset (RDB)</b> is a fully annotated, 12-lead resting-state ECG corpus built for waveform‐level delineation research.<br><b>Origin</b> – RDB is a derivative of the large, open ChapmanECG arrhythmia database (Zheng et al., 2020).<b>Scope</b> – 2 399 recordings, each 10 s long, sampled at 500 Hz.<b>Annotations</b> – Every record is labelled for P-waves, QRS complexes and T-waves on <b>all 12 leads</b>. Initial marks were placed by trained physicians and subsequently reviewed and refined by senior cardiologists; each lead was annotated independently to preserve lead-specific morphology.<b>Rhythm diversity</b> – The set spans atrial fibrillation (AFIB), atrial flutter (AF), atrial tachycardia (AT), supraventricular tachycardia (SVT) and multiple sinus irregularities, providing rich morphological variation for robust model training.<br><br>Rhythm Type Records numAF (Atrial Flutter) 400AFIB (Atrial Fibrillation) 400AT (Atrial Tachycardia) 121SB (Sinus Bradycardia) 400SI (Sinus Irregularity) 399SR (Sinus Rhythm) 400ST (Sinus Tachycardia) 140SVT (Supraventricular Tachycardia) 139Total 2399<br>The combination of high-quality beat-level labels and broad rhythm coverage makes RDB a strong benchmark for developing and evaluating ECG segmentation algorithms that must generalise across diverse clinical presentations.<b>DOI:</b>10.6084/m9.figshare.28892186<b>Citations: </b>Zheng, J., Zhang, J., Danioko, S. <i>et al.</i> A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients. <i>Sci Data</i> 7, 48 (2020). DOI: https://doi.org/10.1038/s41597-020-0386-x.<br>Liu, Y., Zhang, P., Feng, X., Hu, D., Zhou, D., Li, J., ... &amp; Li, Q. (2025). Y-Net-ECG: A Multi-Lead informed and interpretable architecture for ECG segmentation across diverse rhythms. <i>Expert Systems with Applications</i>, 127955. DOI: https://doi.org/10.1016/j.eswa.2025.127955.<br><br>