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	<head>
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	<title>ECG Datasets</title>
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	</head>
	<body>

	<!-- ── Hero ── -->
	<header>
	<div class="badge">ECG Dataset Index</div>
	<h1>ECG Datasets</h1>
	<p>A curated index of 64 publicly available electrocardiogram datasets spanning 12-lead clinical, 3-lead ICU, 2-lead ambulatory, single-lead wearable, and BSPM/ECGI recordings, sourced from open repositories across 15+ countries.</p>
	<div class="links">
	<a href="https://github.com/vlbthambawita/ECGDatasets" target="_blank">
	<svg width="16" height="16" viewBox="0 0 24 24" fill="currentColor"><path d="M12 2C6.477 2 2 6.484 2 12.017c0 4.425 2.865 8.18 6.839 9.504.5.092.682-.217.682-.483 0-.237-.008-.868-.013-1.703-2.782.605-3.369-1.343-3.369-1.343-.454-1.158-1.11-1.466-1.11-1.466-.908-.62.069-.608.069-.608 1.003.07 1.531 1.032 1.531 1.032.892 1.53 2.341 1.088 2.91.832.092-.647.35-1.088.636-1.338-2.22-.253-4.555-1.113-4.555-4.951 0-1.093.39-1.988 1.029-2.688-.103-.253-.446-1.272.098-2.65 0 0 .84-.27 2.75 1.026A9.564 9.564 0 0112 6.844c.85.004 1.705.115 2.504.337 1.909-1.296 2.747-1.027 2.747-1.027.546 1.379.202 2.398.1 2.651.64.7 1.028 1.595 1.028 2.688 0 3.848-2.339 4.695-4.566 4.943.359.309.678.92.678 1.855 0 1.338-.012 2.419-.012 2.747 0 .268.18.58.688.482A10.019 10.019 0 0022 12.017C22 6.484 17.522 2 12 2z"/></svg>
	GitHub
	</a>
	<a href="https://physionet.org/" target="_blank">
	<svg width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M10 13a5 5 0 007.54.54l3-3a5 5 0 00-7.07-7.07l-1.72 1.71"/><path d="M14 11a5 5 0 00-7.54-.54l-3 3a5 5 0 007.07 7.07l1.71-1.71"/></svg>
	PhysioNet
	</a>
	<a href="https://github.com/vlbthambawita/ECGDatasets/issues/new" target="_blank" style="border-color: rgba(239,68,68,0.4); color: #f87171;">
	<svg width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><circle cx="12" cy="12" r="10"/><line x1="12" y1="8" x2="12" y2="12"/><line x1="12" y1="16" x2="12.01" y2="16"/></svg>
	Report an Issue
	</a>
	<a href="ecg_datasets.csv" download style="border-color: rgba(34,197,94,0.4); color: #4ade80;">
	<svg width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M21 15v4a2 2 0 01-2 2H5a2 2 0 01-2-2v-4"/><polyline points="7 10 12 15 17 10"/><line x1="12" y1="15" x2="12" y2="3"/></svg>
	Download CSV
	</a>
	</div>
	<div id="version-badge">
	<span id="vbadge-tag" class="vt"></span>
	<span id="vbadge-sha" class="vs"></span>
	<span id="vbadge-date" class="vs"></span>
	</div>
	</header>

	<!-- ── Stats ── -->
	<section class="stats">
	<div class="stat-card"><div class="num">64</div><div class="label">Total Datasets</div></div>
	<div class="stat-card"><div class="num">24</div><div class="label">12-Lead (PhysioNet)</div></div>
	<div class="stat-card"><div class="num">15</div><div class="label">12-Lead (Other)</div></div>
	<div class="stat-card"><div class="num">10</div><div class="label">2-Lead</div></div>
	<div class="stat-card"><div class="num">10</div><div class="label">1-Lead</div></div>
	<div class="stat-card"><div class="num">11M+</div><div class="label">Max Records</div></div>
	<div class="stat-card"><div class="num">13+</div><div class="label">Countries</div></div>
	</section>

	<!-- ── Controls ── -->
	<div class="controls">
	<div class="search-wrap">
	<svg width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><circle cx="11" cy="11" r="8"/><path d="M21 21l-4.35-4.35"/></svg>
	<input type="text" id="search" placeholder="Search datasets, institutions, countries…" />
	</div>
	<div class="filter-group">
	<button class="filter-btn active" data-filter="all" data-group="access">All</button>
	<button class="filter-btn f-open" data-filter="open" data-group="access">Open</button>
	<button class="filter-btn f-cred" data-filter="credentialed" data-group="access">Credentialed</button>
	<button class="filter-btn f-rest" data-filter="restricted" data-group="access">Restricted</button>
	</div>
	<div class="filter-group">
	<button class="filter-btn active" data-filter="all" data-group="leads">All Leads</button>
	<button class="filter-btn" data-filter="12" data-group="leads">12-Lead</button>
	<button class="filter-btn" data-filter="3" data-group="leads">3-Lead</button>
	<button class="filter-btn" data-filter="2" data-group="leads">2-Lead</button>
	<button class="filter-btn" data-filter="1" data-group="leads">1-Lead</button>
	<button class="filter-btn" data-filter="bspm" data-group="leads">BSPM/ECGI</button>
	</div>
	</div>

	<!-- ── 12-Lead Section Header ── -->
	<div class="section-header">
	<h2>12-Lead ECG Datasets</h2>
	<span class="pill">24 datasets</span>
	</div>

	<!-- ── Table ── -->
	<div class="table-wrap">
	<table id="dataset-table">
	<thead>
	<tr>
	<th>#</th>
	<th>Dataset</th>
	<th>Format</th>
	<th>Patients</th>
	<th>Records</th>
	<th>Access</th>
	<th>Origin</th>
	<th>Paper</th>
	<th>Analysis</th>
	</tr>
	</thead>
	<tbody id="tbody">

	<tr data-access="open" data-leads="12" data-text="ptb-xl germany ptb physikalisch-technische bundesanstalt">
	<td class="num-cell">1</td>
	<td><span class="dataset-name">PTB-XL</span><a class="dataset-link" href="https://physionet.org/content/ptb-xl/1.0.3/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 10 s · 500 Hz (also 100 Hz)</td>
	<td class="count">18,869</td>
	<td class="count">21,799</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">Physikalisch-Technische Bundesanstalt</span><br><span class="origin-country">Germany</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41597-020-0495-6" target="_blank">PTB-XL: A Large Publicly Available ECG Dataset</a></td>
	<td><a class="analysis-link" href="analysis/ptbxl/report.html" target="_blank">📊 View Report</a></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="ptb-xl+ karlsruhe germany features snomed">
	<td class="num-cell">2</td>
	<td><span class="dataset-name">PTB-XL+</span><a class="dataset-link" href="https://physionet.org/content/ptb-xl-plus/1.0.1/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 10 s · 500 Hz · features & median beats</td>
	<td class="count">18,869</td>
	<td class="count">21,799</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">Karlsruhe Institute of Technology</span><br><span class="origin-country">Germany</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41597-023-02153-8" target="_blank">PTB-XL+: A Comprehensive ECG Feature Dataset</a></td>
	<td><a class="analysis-link" href="analysis/ptbxlplus/report.html" target="_blank">📊 View Report</a></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="ptb diagnostic germany berlin benjamin franklin">
	<td class="num-cell">3</td>
	<td><span class="dataset-name">PTB Diagnostic ECG Database</span><a class="dataset-link" href="https://physionet.org/content/ptbdb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>15-lead (12 + 3 Frank) · variable · 1,000 Hz</td>
	<td class="count">290</td>
	<td class="count">549</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Univ. Clinic Benjamin Franklin</span><br><span class="origin-country">Germany — Berlin</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C28C71" target="_blank">Bousseljot et al., Biomedizinische Technik, 1995</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="credentialed" data-leads="12" data-text="mimic iv ecg usa boston beth israel mit">
	<td class="num-cell">4</td>
	<td><span class="dataset-name">MIMIC-IV-ECG</span><a class="dataset-link" href="https://physionet.org/content/mimic-iv-ecg/1.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 10 s · 500 Hz</td>
	<td class="count">~160,000</td>
	<td class="count">~800,000</td>
	<td><span class="tag tag-cred">Credentialed</span><br><small style="color:var(--muted)">PhysioNet DUA</small></td>
	<td><span class="origin-inst">Beth Israel Deaconess Medical Center</span><br><span class="origin-country">USA — Boston, MA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/4nqg-sb35" target="_blank">Gow et al.</a></td>
	<td><a class="analysis-link" href="analysis/mimic_iv_ecg/report.html" target="_blank">📊 View Report</a></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="mimic iv ecg demo usa boston beth israel">
	<td class="num-cell">5</td>
	<td><span class="dataset-name">MIMIC-IV-ECG Demo</span><a class="dataset-link" href="https://physionet.org/content/mimic-iv-ecg-demo/0.1/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 10 s · 500 Hz</td>
	<td class="count">92</td>
	<td class="count">659</td>
	<td><span class="tag tag-open">Open</span></td>
	<td><span class="origin-inst">Beth Israel Deaconess Medical Center</span><br><span class="origin-country">USA — Boston, MA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/4eqn-kt76" target="_blank">Dataset DOI</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="credentialed" data-leads="12" data-text="mimic iv ecg ext icd usa germany mit icd-10">
	<td class="num-cell">6</td>
	<td><span class="dataset-name">MIMIC-IV-ECG-Ext-ICD</span><a class="dataset-link" href="https://physionet.org/content/mimic-iv-ecg-ext-icd-labels/1.0.1/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 10 s · 500 Hz · 1,076 ICD-10-CM codes</td>
	<td class="count-na">Subset of MIMIC-IV-ECG</td>
	<td class="count-na">Subset of MIMIC-IV-ECG</td>
	<td><span class="tag tag-cred">Credentialed</span></td>
	<td><span class="origin-inst">MIT LCP + collaborators</span><br><span class="origin-country">USA / Germany</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1093/ehjdh/ztae039" target="_blank">Eur Heart J Digital Health, 2024</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="chapman shaoxing arrhythmia china usa ningbo">
	<td class="num-cell">7</td>
	<td><span class="dataset-name">Chapman-Shaoxing (Arrhythmia)</span><a class="dataset-link" href="https://physionet.org/content/ecg-arrhythmia/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 10 s · 500 Hz</td>
	<td class="count">45,152</td>
	<td class="count">45,152</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">Chapman Univ.; Shaoxing People's Hospital & Ningbo First Hospital</span><br><span class="origin-country">China / USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41598-020-59821-7" target="_blank">Zheng et al., Scientific Reports, 2020</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="incart st petersburg russia arrhythmia">
	<td class="num-cell">8</td>
	<td><span class="dataset-name">St Petersburg INCART 12-Lead Arrhythmia Database</span><a class="dataset-link" href="https://physionet.org/content/incartdb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 30 min · 257 Hz</td>
	<td class="count">32</td>
	<td class="count">75</td>
	<td><span class="tag tag-open">Open</span></td>
	<td><span class="origin-inst">St. Petersburg Institute of Cardiological Technics (INCART)</span><br><span class="origin-country">Russia</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C2V88N" target="_blank">Dataset DOI</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="ludb lobachevsky russia nizhny novgorod annotated">
	<td class="num-cell">9</td>
	<td><span class="dataset-name">Lobachevsky University ECG Database (LUDB)</span><a class="dataset-link" href="https://physionet.org/content/ludb/1.0.1/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 10 s · 500 Hz · manually annotated waves</td>
	<td class="count">200</td>
	<td class="count">200</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Nizhny Novgorod City Hospital No. 5 / Lobachevsky University</span><br><span class="origin-country">Russia</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1109/ACCESS.2020.3029211" target="_blank">IEEE Access, 2020</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="brugada huca spain asturias hospital">
	<td class="num-cell">10</td>
	<td><span class="dataset-name">Brugada-HUCA</span><a class="dataset-link" href="https://physionet.org/content/brugada-huca/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 12 s · 100 Hz</td>
	<td class="count">363</td>
	<td class="count">363</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY-SA 4.0</small></td>
	<td><span class="origin-inst">Hospital Universitario Central de Asturias (HUCA)</span><br><span class="origin-country">Spain</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/0m2w-dy83" target="_blank">Dataset DOI</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="restricted" data-leads="12" data-text="kurias ecg south korea seoul anam snomed omop">
	<td class="num-cell">11</td>
	<td><span class="dataset-name">KURIAS-ECG</span><a class="dataset-link" href="https://physionet.org/content/kurias-ecg/1.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 10 s · 500 Hz · SNOMED CT + OMOP-CDM</td>
	<td class="count">13,862</td>
	<td class="count">20,000</td>
	<td><span class="tag tag-rest">Restricted</span><br><small style="color:var(--muted)">Pending audit</small></td>
	<td><span class="origin-inst">Korea University Anam Hospital</span><br><span class="origin-country">South Korea — Seoul</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/kga0-0270" target="_blank">Dataset DOI</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="leipzig heart center germany intracardiac electrogram">
	<td class="num-cell">12</td>
	<td><span class="dataset-name">Leipzig Heart Center ECG Database</span><a class="dataset-link" href="https://physionet.org/content/leipzig-heart-center-ecg/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead + intracardiac EGM · variable · 977 Hz</td>
	<td class="count">39</td>
	<td class="count">39</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Leipzig Heart Center</span><br><span class="origin-country">Germany</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/7a4j-vn37" target="_blank">Dataset DOI</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="norwegian athlete ecg norway oslo endurance">
	<td class="num-cell">13</td>
	<td><span class="dataset-name">Norwegian Endurance Athlete ECG Database</span><a class="dataset-link" href="https://physionet.org/content/norwegian-athlete-ecg/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 10 s · 500 Hz</td>
	<td class="count">28</td>
	<td class="count">28</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">University of Oslo</span><br><span class="origin-country">Norway</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/qpjf-gk87" target="_blank">Dataset DOI</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="mhd mri ecg germany magdeburg otto guericke">
	<td class="num-cell">14</td>
	<td><span class="dataset-name">MHD Effect on 12-Lead ECGs in MRI Scanners</span><a class="dataset-link" href="https://physionet.org/content/mhd-effect-ecg-mri/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead + 3-lead · variable · 1,024 Hz</td>
	<td class="count">23</td>
	<td class="count">43</td>
	<td><span class="tag tag-open">Open</span></td>
	<td><span class="origin-inst">Otto-von-Guericke University of Magdeburg</span><br><span class="origin-country">Germany</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/05td-jn37" target="_blank">Krug et al., CinC 2017</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="wilson central terminal australia western sydney campbelltown">
	<td class="num-cell">15</td>
	<td><span class="dataset-name">Wilson Central Terminal ECG Database</span><a class="dataset-link" href="https://physionet.org/content/wctecgdb/1.0.1/" target="_blank">physionet.org ↗</a></td>
	<td>37 signals (12 std + WCT + limb) · 10 s</td>
	<td class="count">92</td>
	<td class="count">540</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">MARCS Institute, Western Sydney Univ.; Campbelltown Hospital</span><br><span class="origin-country">Australia</span></td>
	<td><a class="paper-link" href="https://doi.org/10.3390/machines4040018" target="_blank">Machines, 2016</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="cipa ecg validation usa pharmacology clinical trial">
	<td class="num-cell">16</td>
	<td><span class="dataset-name">CiPA ECG Validation Study</span><a class="dataset-link" href="https://physionet.org/content/ecgcipa/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 10 s</td>
	<td class="count">60</td>
	<td class="count">5,749 segments</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Phase I Clinical Pharmacology Study (NCT03070470)</span><br><span class="origin-country">USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1002/cpt.1303" target="_blank">Clin Pharmacol Ther, 2018</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="ecgdmmld dofetilide moxifloxacin usa pharmacology drug">
	<td class="num-cell">17</td>
	<td><span class="dataset-name">ECG Effects of Dofetilide, Moxifloxacin and Combinations (ECGDMMLD)</span><a class="dataset-link" href="https://physionet.org/content/ecgdmmld/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 10 s · 500 Hz (upsampled to 1 kHz)</td>
	<td class="count">22</td>
	<td class="count">4,211 segments</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">NCT02308748</span><br><span class="origin-country">USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1002/cpt.205" target="_blank">Clin Pharmacol Ther, 2016</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="ecgrdvq ranolazine dofetilide verapamil quinidine usa pharmacology drug">
	<td class="num-cell">18</td>
	<td><span class="dataset-name">ECG Effects of Ranolazine, Dofetilide, Verapamil, Quinidine (ECGRDVQ)</span><a class="dataset-link" href="https://physionet.org/content/ecgrdvq/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 10 s · 500 Hz</td>
	<td class="count">22</td>
	<td class="count">5,232 segments</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Clinical Pharmacology Study</span><br><span class="origin-country">USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/clpt.2014.155" target="_blank">Clin Pharmacol Ther, 2014</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="eye tracking ecg qatar hamad bin khalifa interpretation">
	<td class="num-cell">19</td>
	<td><span class="dataset-name">Eye Tracking Dataset for 12-Lead ECG Interpretation</span><a class="dataset-link" href="https://physionet.org/content/eye-tracking-ecg/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead ECG images · eye tracking at 60 Hz</td>
	<td class="count">63 interpreters</td>
	<td class="count">630 sessions</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC ODbL</small></td>
	<td><span class="origin-inst">Qatar Biomedical Research Institute, Hamad bin Khalifa Univ.</span><br><span class="origin-country">Qatar</span></td>
	<td><a class="paper-link" href="http://dx.doi.org/10.2196/34058" target="_blank">JMIR, 2022</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="restricted" data-leads="12" data-text="echonext columbia usa new york echocardiography">
	<td class="num-cell">20</td>
	<td><span class="dataset-name">EchoNext</span><a class="dataset-link" href="https://physionet.org/content/echonext/1.1.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 10 s · 250 Hz</td>
	<td class="count-na">Not disclosed</td>
	<td class="count">100,000</td>
	<td><span class="tag tag-rest">Restricted</span></td>
	<td><span class="origin-inst">Columbia University Irving Medical Center</span><br><span class="origin-country">USA — New York, NY</span></td>
	<td><span class="no-paper">Poterucha et al., Nature, 2025</span></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="credentialed" data-leads="12" data-text="symile mimic multimodal ecg cxr labs usa mit bidmc neurips">
	<td class="num-cell">21</td>
	<td><span class="dataset-name">Symile-MIMIC</span><a class="dataset-link" href="https://physionet.org/content/symile-mimic/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 10 s · 500 Hz · multimodal (ECG + CXR + labs)</td>
	<td class="count">9,573</td>
	<td class="count">11,622</td>
	<td><span class="tag tag-cred">Credentialed</span></td>
	<td><span class="origin-inst">MIT LCP / BIDMC</span><br><span class="origin-country">USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/3vvj-s428" target="_blank">Saporta et al., NeurIPS 2024</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="cinc challenge 2020 physionet china russia germany usa cpsc georgia">
	<td class="num-cell">22</td>
	<td><span class="dataset-name">PhysioNet/CinC Challenge 2020</span><a class="dataset-link" href="https://physionet.org/content/challenge-2020/1.0.2/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · 6–60 s · 257–1,000 Hz</td>
	<td class="count-na">—</td>
	<td class="count">~52,501</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">CPSC, INCART, PTB, PTB-XL, Georgia</span><br><span class="origin-country">Multi-national (China, Russia, Germany, USA)</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1088/1361-6579/abc960" target="_blank">Physiol Meas, 2020</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="cinc challenge 2021 physionet china russia germany usa michigan chapman ningbo">
	<td class="num-cell">23</td>
	<td><span class="dataset-name">PhysioNet/CinC Challenge 2021</span><a class="dataset-link" href="https://physionet.org/content/challenge-2021/1.0.3/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead (+ reduced-lead) · 5–144 s · 250–1,000 Hz</td>
	<td class="count-na">—</td>
	<td class="count">~130,862</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">CPSC, INCART, PTB-XL, Georgia, Chapman-Shaoxing, Ningbo, UMich</span><br><span class="origin-country">Multi-national (China, Russia, Germany, USA)</span></td>
	<td><a class="paper-link" href="https://doi.org/10.23919/CinC53138.2021.9662687" target="_blank">CinC 2021</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="staff iii staffiii ptca balloon ischemia exercise stress coronary angiography charleston usa sweden">
	<td class="num-cell">24</td>
	<td><span class="dataset-name">STAFF III Database</span><a class="dataset-link" href="https://physionet.org/content/staffiii/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>12-lead · variable duration · 1,000 Hz · 0.625 µV resolution · WFDB</td>
	<td class="count">104</td>
	<td class="count">152 inflations</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Charleston Area Medical Center; Blekinge Hospital</span><br><span class="origin-country">USA / Sweden</span></td>
	<td><a class="paper-link" href="https://doi.org/10.22489/CinC.2017.266-133" target="_blank">Martínez et al., CinC 2017</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	</tbody>
	</table>
	<div id="no-results">No datasets match your search.</div>
	</div>

	<!-- ── Other Repos Section Header ── -->
	<div class="section-header">
	<h2>12-Lead ECG Datasets (Other Repositories)</h2>
	<span class="pill">15 datasets</span>
	</div>

	<div class="table-wrap">
	<table id="other-repos-table">
	<thead>
	<tr>
	<th>#</th>
	<th>Dataset</th>
	<th>Format</th>
	<th>Patients</th>
	<th>Records</th>
	<th>Access</th>
	<th>Origin</th>
	<th>Paper</th>
	<th>Analysis</th>
	</tr>
	</thead>
	<tbody id="tbody2">

	<tr data-access="open" data-leads="12" data-text="cpsc 2018 china physiological signal challenge icbeb nanjing arrhythmia matlab">
	<td class="num-cell">1</td>
	<td><span class="dataset-name">CPSC 2018 (China Physiological Signal Challenge 2018)</span><a class="dataset-link" href="http://2018.icbeb.org/Challenge.html" target="_blank">icbeb.org ↗</a></td>
	<td>12-lead · 6–60 s · 500 Hz · MATLAB .mat</td>
	<td class="count">~6,877</td>
	<td class="count">6,877</td>
	<td><span class="tag tag-open">Open</span></td>
	<td><span class="origin-inst">11 hospitals (ICBEB, Nanjing)</span><br><span class="origin-country">China</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1166/jmihi.2018.2442" target="_blank">Liu et al., J. Med. Imaging Health Inform., 2018</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="chapman shaoxing ecg figshare arrhythmia 10646 china usa">
	<td class="num-cell">2</td>
	<td><span class="dataset-name">Chapman-Shaoxing ECG Database (10,646 patients)</span><a class="dataset-link" href="https://doi.org/10.6084/m9.figshare.c.4560497.v2" target="_blank">figshare.com ↗</a></td>
	<td>12-lead · 10 s · 500 Hz · CSV</td>
	<td class="count">10,646</td>
	<td class="count">10,646</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">Chapman University; Shaoxing People's Hospital</span><br><span class="origin-country">China / USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41597-020-0386-x" target="_blank">Zheng et al., Scientific Data, 2020</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="ningbo first hospital ecg idiopathic ventricular arrhythmia iva figshare china chapman ablation">
	<td class="num-cell">3</td>
	<td><span class="dataset-name">Ningbo First Hospital ECG Database (Idiopathic Ventricular Arrhythmia)</span><a class="dataset-link" href="https://doi.org/10.6084/m9.figshare.c.4668086.v2" target="_blank">figshare.com ↗</a></td>
	<td>12-lead · 10 s · 500 Hz · CSV</td>
	<td class="count">334</td>
	<td class="count">334</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">Chapman University; Ningbo First Hospital, Zhejiang University</span><br><span class="origin-country">China / USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41597-020-0440-8" target="_blank">Zheng et al., Scientific Data, 2020</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="shandong provincial hospital sphdb ecg hdf5 figshare china aha multi-label">
	<td class="num-cell">4</td>
	<td><span class="dataset-name">Shandong Provincial Hospital ECG Database (SPHDB)</span><a class="dataset-link" href="https://doi.org/10.6084/m9.figshare.c.5779802.v1" target="_blank">figshare.com ↗</a></td>
	<td>12-lead · 10–60 s · 500 Hz · HDF5</td>
	<td class="count">24,666</td>
	<td class="count">25,770</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">Shandong Provincial Hospital</span><br><span class="origin-country">China</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41597-022-01403-5" target="_blank">Liu et al., Scientific Data, 2022</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="code 15 percent telehealth minas gerais brazil tnmg zenodo hdf5 deep learning ribeiro">
	<td class="num-cell">5</td>
	<td><span class="dataset-name">CODE-15% (Telehealth Network of Minas Gerais, 15% subset)</span><a class="dataset-link" href="https://doi.org/10.5281/zenodo.4916206" target="_blank">zenodo.org ↗</a></td>
	<td>12-lead · ~10 s · 400 Hz · HDF5</td>
	<td class="count">233,770</td>
	<td class="count">345,779</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">Telehealth Network of Minas Gerais (TNMG)</span><br><span class="origin-country">Brazil</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41467-020-15432-4" target="_blank">Ribeiro et al., Nature Communications, 2020</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="code test 827 zenodo hdf5 brazil minas gerais tnmg ribeiro hold-out evaluation">
	<td class="num-cell">6</td>
	<td><span class="dataset-name">CODE-test (827-record hold-out test set)</span><a class="dataset-link" href="https://doi.org/10.5281/zenodo.3765780" target="_blank">zenodo.org ↗</a></td>
	<td>12-lead · 7–10 s · 400 Hz · HDF5</td>
	<td class="count">827</td>
	<td class="count">827</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">Universidade Federal de Minas Gerais / TNMG</span><br><span class="origin-country">Brazil</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41467-020-15432-4" target="_blank">Ribeiro et al., Nature Communications, 2020</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="restricted" data-leads="12" data-text="code full dataset scilifelab figshare brazil tnmg 2 million hdf5 dua">
	<td class="num-cell">7</td>
	<td><span class="dataset-name">CODE (Full Dataset, ~2.3M records)</span><a class="dataset-link" href="https://figshare.scilifelab.se/articles/dataset/CODE_dataset/15169716" target="_blank">scilifelab.se ↗</a></td>
	<td>12-lead · 400 Hz · HDF5</td>
	<td class="count">~1,676,384</td>
	<td class="count">~2,322,513</td>
	<td><span class="tag tag-rest">Restricted</span><br><small style="color:var(--muted)">DUA required</small></td>
	<td><span class="origin-inst">Telehealth Network of Minas Gerais (TNMG)</span><br><span class="origin-country">Brazil</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41467-020-15432-4" target="_blank">Ribeiro et al., Nature Communications, 2020</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="sami trop chagas cardiomyopathy brazil minas gerais zenodo hdf5 mortality age">
	<td class="num-cell">8</td>
	<td><span class="dataset-name">SaMi-Trop (Chagas Cardiomyopathy Cohort)</span><a class="dataset-link" href="https://doi.org/10.5281/zenodo.4905618" target="_blank">zenodo.org ↗</a></td>
	<td>12-lead · 400 Hz · HDF5</td>
	<td class="count">1,631</td>
	<td class="count">1,631</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">UFMG; Uppsala University; EPFL</span><br><span class="origin-country">Brazil / Sweden / Switzerland</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1101/2021.02.19.21251232" target="_blank">Lima et al., medRxiv, 2021</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="ikem prague czech republic institute clinical experimental medicine zenodo hdf5 cardiology diabetes">
	<td class="num-cell">9</td>
	<td><span class="dataset-name">IKEM Dataset (Institute for Clinical and Experimental Medicine, Prague)</span><a class="dataset-link" href="https://doi.org/10.5281/zenodo.8393007" target="_blank">zenodo.org ↗</a></td>
	<td>12-lead (stored as 8 reduced leads) · 10 s · 500 Hz · HDF5</td>
	<td class="count">30,290</td>
	<td class="count">98,130</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">IKEM (Institute for Clinical and Experimental Medicine)</span><br><span class="origin-country">Czech Republic — Prague</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1016/j.knosys.2023.111014" target="_blank">Seják et al., Knowledge-Based Systems, 2023</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="medalcare xl synthetic simulation electrophysiological zenodo austria germany uk graz kit ptb edinburgh">
	<td class="num-cell">10</td>
	<td><span class="dataset-name">MedalCare-XL (Synthetic 12-Lead ECGs from Simulations)</span><a class="dataset-link" href="https://doi.org/10.5281/zenodo.8068944" target="_blank">zenodo.org ↗</a></td>
	<td>12-lead · 10 s · 500 Hz · CSV (raw/noise/filtered variants)</td>
	<td class="count-na">0 (synthetic)</td>
	<td class="count">16,900</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">Medical Univ. of Graz; KIT; PTB; Univ. of Edinburgh</span><br><span class="origin-country">Austria / Germany / UK</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41597-023-02416-4" target="_blank">Gillette et al., Scientific Data, 2023</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="credentialed" data-leads="12" data-text="harvard emory ecg heedb bdsp aws wfdb massachusetts general hospital mgh emory atlanta usa largest">
	<td class="num-cell">11</td>
	<td><span class="dataset-name">Harvard-Emory ECG Database (HEEDB)</span><a class="dataset-link" href="https://bdsp.io/content/heedb/5.0/" target="_blank">bdsp.io ↗</a></td>
	<td>12-lead · 10 s · 250/500 Hz · WFDB</td>
	<td class="count">2,167,795</td>
	<td class="count">11,607,261</td>
	<td><span class="tag tag-cred">Credentialed</span><br><small style="color:var(--muted)">DUA (BDSP)</small></td>
	<td><span class="origin-inst">Massachusetts General Hospital; Emory University Hospital</span><br><span class="origin-country">USA — Boston & Atlanta</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41597-026-06861-9" target="_blank">Koscova et al., Scientific Data, 2026</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="restricted" data-leads="12" data-text="nightingale bwh brigham women hospital emergency department ecg boston usa numpy cardiac risk">
	<td class="num-cell">12</td>
	<td><span class="dataset-name">Nightingale BWH Emergency Dept ECG Dataset</span><a class="dataset-link" href="https://docs.ngsci.org/datasets/ed-bwh-ecg/" target="_blank">ngsci.org ↗</a></td>
	<td>12-lead · 100 Hz · NumPy arrays</td>
	<td class="count">30,933</td>
	<td class="count">103,952</td>
	<td><span class="tag tag-rest">Restricted</span><br><small style="color:var(--muted)">Institutional credentials</small></td>
	<td><span class="origin-inst">Brigham and Women's Hospital</span><br><span class="origin-country">USA — Boston, MA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1093/qje/qjab046" target="_blank">Mullainathan & Obermeyer, QJE, 2021</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="restricted" data-leads="12" data-text="nightingale ntuh national taiwan university hospital cardiac arrest emergency xml taiwan">
	<td class="num-cell">13</td>
	<td><span class="dataset-name">Nightingale NTUH Cardiac Arrest ECG Dataset</span><a class="dataset-link" href="https://docs.ngsci.org/datasets/arrest-ntuh-ecg/" target="_blank">ngsci.org ↗</a></td>
	<td>12-lead · ~500 Hz · XML/array</td>
	<td class="count">10,950</td>
	<td class="count">18,072</td>
	<td><span class="tag tag-rest">Restricted</span><br><small style="color:var(--muted)">Institutional credentials</small></td>
	<td><span class="origin-inst">National Taiwan University Hospital, Emergency Dept</span><br><span class="origin-country">Taiwan</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41591-022-01804-4" target="_blank">Obermeyer et al., Nature Medicine, 2022</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="gu ecg gazi university turkey ptca ischaemia mendeley high frequency bilkent coronary artery">
	<td class="num-cell">14</td>
	<td><span class="dataset-name">GU-ECG (Gazi University, PTCA-induced Ischaemia)</span><a class="dataset-link" href="https://doi.org/10.17632/zhr5zsngtg.1" target="_blank">mendeley.com ↗</a></td>
	<td>12-lead continuous · 8,800 Hz · 24-bit · .ekg format</td>
	<td class="count">74</td>
	<td class="count">222</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">Gazi University Faculty of Medicine; Bilkent University</span><br><span class="origin-country">Turkey</span></td>
	<td><a class="paper-link" href="https://doi.org/10.17632/zhr5zsngtg.1" target="_blank">Dataset DOI</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="12" data-text="zzu pecg zhengzhou pediatric children ecg figshare wfdb china kawasaki myocarditis congenital">
	<td class="num-cell">15</td>
	<td><span class="dataset-name">ZZU pECG (Zhengzhou University Pediatric ECG Database)</span><a class="dataset-link" href="https://doi.org/10.6084/m9.figshare.27078763" target="_blank">figshare.com ↗</a></td>
	<td>12-lead + 9-lead · 5–120 s · 500 Hz · WFDB</td>
	<td class="count">11,643 children</td>
	<td class="count">14,190</td>
	<td><span class="tag tag-open">Open</span></td>
	<td><span class="origin-inst">First Affiliated Hospital of Zhengzhou University</span><br><span class="origin-country">China</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41597-025-05225-z" target="_blank">Scientific Data, 2025</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	</tbody>
	</table>
	</div>

	<!-- ── 2-Lead Section Header ── -->
	<div class="section-header">
	<h2>2-Lead ECG Datasets</h2>
	<span class="pill">12 datasets</span>
	</div>

	<div class="table-wrap">
	<table id="two-lead-table">
	<thead>
	<tr>
	<th>#</th>
	<th>Dataset</th>
	<th>Format</th>
	<th>Patients</th>
	<th>Records</th>
	<th>Access</th>
	<th>Origin</th>
	<th>Paper</th>
	<th>Analysis</th>
	</tr>
	</thead>
	<tbody id="tbody3">

	<tr data-access="open" data-leads="2" data-text="mit-bih arrhythmia usa beth israel hospital mit mlii v1 holter ambulatory benchmark annotations">
	<td class="num-cell">1</td>
	<td><span class="dataset-name">MIT-BIH Arrhythmia Database</span><a class="dataset-link" href="https://physionet.org/content/mitdb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>2-lead (MLII + V1) · 30 min · 360 Hz · WFDB</td>
	<td class="count">47</td>
	<td class="count">48</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Beth Israel Hospital / MIT</span><br><span class="origin-country">USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C2F305" target="_blank">Moody & Mark, IEEE EMBS 2001</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="2" data-text="mit-bih atrial fibrillation afdb af flutter usa beth israel hospital holter rhythm">
	<td class="num-cell">2</td>
	<td><span class="dataset-name">MIT-BIH Atrial Fibrillation Database</span><a class="dataset-link" href="https://physionet.org/content/afdb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>2-lead · 10 h · 250 Hz · WFDB</td>
	<td class="count">25</td>
	<td class="count">25</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Beth Israel Hospital</span><br><span class="origin-country">USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C2MW2D" target="_blank">Moody & Mark, CinC 1983</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="2" data-text="long-term af ltafdb atrial fibrillation paroxysmal sustained northwestern usa poland medicalgorithmics holter 24h">
	<td class="num-cell">3</td>
	<td><span class="dataset-name">Long-Term AF Database (LTAFDB)</span><a class="dataset-link" href="https://physionet.org/content/ltafdb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>2-lead · 24–25 h · 128 Hz · WFDB</td>
	<td class="count">84</td>
	<td class="count">84</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Northwestern University; MEDICALgorithmics</span><br><span class="origin-country">USA / Poland</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C2QG6Q" target="_blank">Petrutiu et al., Europace 2007</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="2" data-text="mit-bih normal sinus rhythm nsrdb healthy control usa beth israel hospital holter 24h">
	<td class="num-cell">4</td>
	<td><span class="dataset-name">MIT-BIH Normal Sinus Rhythm Database</span><a class="dataset-link" href="https://physionet.org/content/nsrdb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>2-lead · ~24 h · 128 Hz · WFDB</td>
	<td class="count">18</td>
	<td class="count">18</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Beth Israel Hospital</span><br><span class="origin-country">USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C2NK5R" target="_blank">Dataset DOI</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="2" data-text="mit-bih supraventricular arrhythmia svdb mlii v1 usa mit harvard-mit hst svt pac pjc">
	<td class="num-cell">5</td>
	<td><span class="dataset-name">MIT-BIH Supraventricular Arrhythmia Database</span><a class="dataset-link" href="https://physionet.org/content/svdb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>2-lead (MLII + V1) · 30 min · 360 Hz · WFDB</td>
	<td class="count-na">—</td>
	<td class="count">78</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">MIT / Harvard-MIT HST</span><br><span class="origin-country">USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C2V30W" target="_blank">Greenwald, PhD thesis, Harvard-MIT 1990</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="2" data-text="european st-t edb ischemia st segment t-wave italy pisa cnr esc ambulatory holter">
	<td class="num-cell">6</td>
	<td><span class="dataset-name">European ST-T Database (EDB)</span><a class="dataset-link" href="https://physionet.org/content/edb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>2-lead ambulatory · 2 h · 250 Hz · WFDB</td>
	<td class="count">79</td>
	<td class="count">90</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">CNR Institute for Clinical Physiology, Pisa; European Society of Cardiology</span><br><span class="origin-country">Italy</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C2D59Z" target="_blank">Taddei et al., Eur Heart J 1992</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="2" data-text="bidmc congestive heart failure chfdb nyha usa boston beth israel deaconess medical center holter 20h">
	<td class="num-cell">7</td>
	<td><span class="dataset-name">BIDMC Congestive Heart Failure Database</span><a class="dataset-link" href="https://physionet.org/content/chfdb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>2-lead · ~20 h · 250 Hz · WFDB</td>
	<td class="count">15</td>
	<td class="count">15</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Beth Israel Deaconess Medical Center</span><br><span class="origin-country">USA — Boston, MA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C29G60" target="_blank">Baim et al., J Am Coll Cardiol 1986</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="2" data-text="sudden cardiac death holter sddb ventricular tachycardia vt vf usa mit scd arrhythmia">
	<td class="num-cell">8</td>
	<td><span class="dataset-name">Sudden Cardiac Death Holter Database</span><a class="dataset-link" href="https://physionet.org/content/sddb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>2-lead · 4–25 h · 250 Hz · WFDB</td>
	<td class="count">23</td>
	<td class="count">23</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">MIT</span><br><span class="origin-country">USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C2W306" target="_blank">Greenwald, MS thesis, MIT 1986</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="2" data-text="qt database qtdb waveform boundary p qrs t u wave annotation usa mit physionet benchmark">
	<td class="num-cell">9</td>
	<td><span class="dataset-name">QT Database (QTDB)</span><a class="dataset-link" href="https://physionet.org/content/qtdb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>2-lead · 15 min · various Hz · WFDB</td>
	<td class="count-na">—</td>
	<td class="count">105</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">MIT / PhysioNet</span><br><span class="origin-country">USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C24K53" target="_blank">Laguna et al., CinC 1997</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="2" data-text="shdb-af saitama holter atrial fibrillation japan cc5 nasa lead paroxysmal deep learning generalization">
	<td class="num-cell">10</td>
	<td><span class="dataset-name">SHDB-AF (Saitama Holter Database — Atrial Fibrillation)</span><a class="dataset-link" href="https://physionet.org/content/shdb-af/1.0.1/" target="_blank">physionet.org ↗</a></td>
	<td>2-lead (CC5 + NASA) · ~24 h · 125 Hz · WFDB</td>
	<td class="count">122</td>
	<td class="count">128</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Saitama Medical University International Medical Center</span><br><span class="origin-country">Japan</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/n6yq-fq90" target="_blank">Tsutsui et al., Scientific Data 2025</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="2" data-text="mit-bih st change stdb exercise stress test st depression elevation transient ischemia usa mit physionet">
	<td class="num-cell">11</td>
	<td><span class="dataset-name">MIT-BIH ST Change Database</span><a class="dataset-link" href="https://physionet.org/content/stdb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>2-lead · variable length · 360 Hz · WFDB · mostly exercise stress ECGs</td>
	<td class="count-na">—</td>
	<td class="count">28</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">MIT / PhysioNet</span><br><span class="origin-country">USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C2ZW2H" target="_blank">Dataset DOI</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="2" data-text="long-term st ltstdb ischemia st episode ambulatory holter 24h ischaemia multi-national eu ljubljana pisa cambridge">
	<td class="num-cell">12</td>
	<td><span class="dataset-name">Long-Term ST Database (LTSTDB)</span><a class="dataset-link" href="https://physionet.org/content/ltstdb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>2–3 lead · 21–24 h · 250 Hz · WFDB · annotated ST episodes</td>
	<td class="count">80</td>
	<td class="count">86</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Ljubljana; Pisa; Cambridge</span><br><span class="origin-country">Multi-national (EU)</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C2CC7C" target="_blank">Jager et al., Med Biol Eng Comput, 2003</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	</tbody>
	</table>
	</div>

	<!-- ── 1-Lead Section Header ── -->
	<div class="section-header">
	<h2>1-Lead ECG Datasets</h2>
	<span class="pill">10 datasets</span>
	</div>

	<div class="table-wrap">
	<table id="single-lead-table">
	<thead>
	<tr>
	<th>#</th>
	<th>Dataset</th>
	<th>Format</th>
	<th>Patients</th>
	<th>Records</th>
	<th>Access</th>
	<th>Origin</th>
	<th>Paper</th>
	<th>Analysis</th>
	</tr>
	</thead>
	<tbody id="tbody1">

	<tr data-access="open" data-leads="1" data-text="icentia11k canada montreal arrhythmia cardiostat wearable continuous">
	<td class="num-cell">1</td>
	<td><span class="dataset-name">Icentia11k Single Lead Continuous ECG</span><a class="dataset-link" href="https://physionet.org/content/icentia11k-continuous-ecg/1.0/" target="_blank">physionet.org ↗</a></td>
	<td>1-lead (modified Lead I) · ~70 min/seg · 250 Hz</td>
	<td class="count">11,000</td>
	<td class="count">541,794 segments</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY-NC-SA 4.0</small></td>
	<td><span class="origin-inst">Université de Montréal; Icentia Inc.</span><br><span class="origin-country">Canada</span></td>
	<td><a class="paper-link" href="https://arxiv.org/abs/1910.09570" target="_blank">Tan et al., CinC 2021</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="1" data-text="cinc challenge 2017 af atrial fibrillation alivecor usa mit harvard">
	<td class="num-cell">2</td>
	<td><span class="dataset-name">PhysioNet/CinC Challenge 2017 (AF Classification)</span><a class="dataset-link" href="https://physionet.org/content/challenge-2017/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>1-lead (AliveCor) · 9–61 s · 300 Hz</td>
	<td class="count-na">—</td>
	<td class="count">12,186</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution (training)</small></td>
	<td><span class="origin-inst">AliveCor Inc. / MIT-Harvard PhysioNet</span><br><span class="origin-country">USA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.22489/CinC.2017.065-469" target="_blank">Clifford et al., CinC 2017</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="1" data-text="apnea ecg sleep germany marburg philipps overnight holter">
	<td class="num-cell">3</td>
	<td><span class="dataset-name">Apnea-ECG Database</span><a class="dataset-link" href="https://physionet.org/content/apnea-ecg/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>1-lead · 7–10 h overnight · 100 Hz</td>
	<td class="count">~70</td>
	<td class="count">70</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Philipps-University Marburg</span><br><span class="origin-country">Germany</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C23W2R" target="_blank">Penzel et al., CinC 2000</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="1" data-text="ecg id biometric russia leti saint petersburg wrist lead i identification">
	<td class="num-cell">4</td>
	<td><span class="dataset-name">ECG-ID Database</span><a class="dataset-link" href="https://physionet.org/content/ecgiddb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>1-lead (Lead I, wrist) · 20 s · 500 Hz</td>
	<td class="count">90</td>
	<td class="count">310</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Electrotechnical University "LETI"</span><br><span class="origin-country">Russia — St. Petersburg</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C2J01F" target="_blank">Lugovaya, MSc thesis, 2005</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="1" data-text="post ictal epilepsy seizure usa boston beth israel harvard heart rate">
	<td class="num-cell">5</td>
	<td><span class="dataset-name">Post-Ictal Heart Rate Oscillations in Partial Epilepsy</span><a class="dataset-link" href="https://physionet.org/content/szdb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>1-lead · overnight continuous · 200 Hz</td>
	<td class="count">5</td>
	<td class="count">7</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">Beth Israel Deaconess Medical Center / Harvard</span><br><span class="origin-country">USA — Boston, MA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C2QC72" target="_blank">Al-Aweel et al., Neurology 1999</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="1" data-text="toilet tollet thigh ecg portugal lisbon dry electrode wearable bmi">
	<td class="num-cell">6</td>
	<td><span class="dataset-name">tOLIet (Thigh-based ECG, toilet seat)</span><a class="dataset-link" href="https://physionet.org/content/tollet/1.0.1/" target="_blank">physionet.org ↗</a></td>
	<td>1-lead (thigh, dry polymer electrodes) · up to 5 min · 1,000 Hz</td>
	<td class="count">86</td>
	<td class="count">149</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">Centro Hospitalar Universitário de Lisboa Central (CHULC)</span><br><span class="origin-country">Portugal — Lisbon</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41597-026-06713-6" target="_blank">Silva et al., Scientific Data 2026</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="1" data-text="but qdb brno ecg quality wearable czech republic bittium faros ambulatory free-living">
	<td class="num-cell">7</td>
	<td><span class="dataset-name">Brno University of Technology ECG Quality Database (BUT QDB)</span><a class="dataset-link" href="https://physionet.org/content/butqdb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>1-lead (Bittium Faros 180) + 3-axis accel. · ≥24 h · 1,000 Hz</td>
	<td class="count">15</td>
	<td class="count">18</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">Brno University of Technology</span><br><span class="origin-country">Czech Republic</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1109/tbme.2020.2969719" target="_blank">Smital et al., IEEE TBME 2020</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="1" data-text="vitaldb arrhythmia south korea seoul intraoperative lead ii surgical anesthesia">
	<td class="num-cell">8</td>
	<td><span class="dataset-name">VitalDB Arrhythmia Database</span><a class="dataset-link" href="https://physionet.org/content/vitaldb-arrhythmia/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>1-lead (Lead II, intraoperative) · ~20 min median · 500 Hz</td>
	<td class="count">482</td>
	<td class="count">482</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">CC BY 4.0</small></td>
	<td><span class="origin-inst">Seoul National University Hospital</span><br><span class="origin-country">South Korea</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/s41597-026-07076-8" target="_blank">Eun et al., Scientific Data 2026</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="1" data-text="picsdb preterm infant cardio respiratory usa umass worcester nicu apnea bradycardia">
	<td class="num-cell">9</td>
	<td><span class="dataset-name">Preterm Infant Cardio-Respiratory Signals Database (PICSDB)</span><a class="dataset-link" href="https://physionet.org/content/picsdb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>1-lead (single channel from bedside monitor) · 20–70 h · 500 Hz</td>
	<td class="count">10 infants</td>
	<td class="count">10</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">UMass Memorial Healthcare NICU</span><br><span class="origin-country">USA — Worcester, MA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1109/TBME.2016.2632746" target="_blank">Shamout et al., IEEE TBME 2017</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="restricted" data-leads="1" data-text="smartwatch ecg lead i spain apple samsung fitbit withings synthetic simulator">
	<td class="num-cell">10</td>
	<td><span class="dataset-name">ECG-Capable Smartwatches Dataset</span><a class="dataset-link" href="https://physionet.org/content/ecg-capable-smartwatches/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>1-lead (Lead I) · 10 s · 4 smartwatch models + reference (synthetic)</td>
	<td class="count-na">0 (synthetic)</td>
	<td class="count">915</td>
	<td><span class="tag tag-rest">Restricted</span><br><small style="color:var(--muted)">DUA required</small></td>
	<td><span class="origin-inst">Instituto Ramón y Cajal de Investigación Sanitaria</span><br><span class="origin-country">Spain</span></td>
	<td><span class="no-paper">Recas et al. (pending)</span></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	</tbody>
	</table>
	</div>

	<!-- ── 3-Lead Section Header ── -->
	<div class="section-header">
	<h2>3-Lead ECG Datasets</h2>
	<span class="pill">2 datasets</span>
	</div>

	<div class="table-wrap">
	<table id="three-lead-table">
	<thead>
	<tr>
	<th>#</th>
	<th>Dataset</th>
	<th>Format</th>
	<th>Patients</th>
	<th>Records</th>
	<th>Access</th>
	<th>Origin</th>
	<th>Paper</th>
	<th>Analysis</th>
	</tr>
	</thead>
	<tbody id="tbody4">

	<tr data-access="open" data-leads="3" data-text="ucddb ucd sleep apnea dublin ireland holter v5 cc5 v5r overnight polysomnogram psg 3-lead">
	<td class="num-cell">1</td>
	<td><span class="dataset-name">St. Vincent's / UCD Sleep Apnea Database (UCDDB)</span><a class="dataset-link" href="https://physionet.org/content/ucddb/1.0.0/" target="_blank">physionet.org ↗</a></td>
	<td>3-lead Holter (V5, CC5, V5R) · overnight PSG · 128 Hz · EDF</td>
	<td class="count">25</td>
	<td class="count">25</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODC Attribution</small></td>
	<td><span class="origin-inst">St. Vincent's University Hospital / University College Dublin</span><br><span class="origin-country">Ireland</span></td>
	<td><a class="paper-link" href="https://doi.org/10.13026/C26C7D" target="_blank">Dataset DOI</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	<tr data-access="open" data-leads="3" data-text="mimic iii waveform icu monitoring 3-lead usa boston beth israel bidmc continuous lead ii v avr mcl">
	<td class="num-cell">2</td>
	<td><span class="dataset-name">MIMIC-III Waveform Database Matched Subset</span><a class="dataset-link" href="https://physionet.org/content/mimic3wdb-matched/1.0/" target="_blank">physionet.org ↗</a></td>
	<td>1–5 ECG leads · typically 3-lead ICU (Lead II, V, AVR) · continuous · 125 Hz · WFDB</td>
	<td class="count">10,282</td>
	<td class="count">22,317</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">ODbL</small></td>
	<td><span class="origin-inst">Beth Israel Deaconess Medical Center</span><br><span class="origin-country">USA — Boston, MA</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1038/sdata.2016.35" target="_blank">Johnson et al., Scientific Data, 2016</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	</tbody>
	</table>
	</div>

	<!-- ── BSPM / ECGI Section Header ── -->
	<div class="section-header">
	<h2>BSPM / ECGI Datasets</h2>
	<span class="pill">1 dataset</span>
	</div>

	<div class="table-wrap">
	<table id="bspm-table">
	<thead>
	<tr>
	<th>#</th>
	<th>Dataset</th>
	<th>Format</th>
	<th>Subjects</th>
	<th>Records</th>
	<th>Access</th>
	<th>Origin</th>
	<th>Paper</th>
	<th>Analysis</th>
	</tr>
	</thead>
	<tbody id="tbody5">

	<tr data-access="open" data-leads="bspm" data-text="edgar bspm body surface potential mapping ecgi electrocardiographic imaging utah sci institute geometry torso ct simulation human canine">
	<td class="num-cell">1</td>
	<td><span class="dataset-name">EDGAR (Experimental Data & Geometric Analysis Repository)</span><a class="dataset-link" href="https://www.ecg-imaging.org/edgar-database" target="_blank">ecg-imaging.org ↗</a></td>
	<td>BSPM (64+ leads) + torso geometry + CT · human, canine & simulation · MATLAB/SCIRun</td>
	<td class="count">Multiple</td>
	<td class="count">Multiple datasets</td>
	<td><span class="tag tag-open">Open</span><br><small style="color:var(--muted)">Free registration</small></td>
	<td><span class="origin-inst">Univ. of Utah; Charles Univ. Hospital; Karlsruhe Institute of Technology</span><br><span class="origin-country">Multi-national (USA / Czech Republic / Germany)</span></td>
	<td><a class="paper-link" href="https://doi.org/10.1016/j.jelectrocard.2015.08.008" target="_blank">Aras et al., J Electrocardiol, 2015</a></td>
	<td><span class="analysis-soon">🕑 Coming soon</span></td>
	</tr>

	</tbody>
	</table>
	</div>

	<!-- ── Statistics Section ── -->
	<hr class="section-divider" style="margin-top:0">
	<section class="charts-section">
	<div class="charts-section-title">Dataset Statistics</div>
	<div class="charts-section-sub">Interactive visualisations derived from the full 64-dataset catalogue</div>
	<div class="charts-grid">

	<div class="chart-card">
	<h3>Datasets by Lead Category</h3>
	<p>Distribution across the four lead-count groups</p>
	<div id="chart-lead" class="plotly-chart"></div>
	</div>

	<div class="chart-card">
	<h3>Access Type Breakdown</h3>
	<p>Open vs credentialed vs restricted across all datasets</p>
	<div id="chart-access" class="plotly-chart"></div>
	</div>

	<div class="chart-card tall">
	<h3>Datasets by Country of Origin</h3>
	<p>Primary country attributed to each dataset (multi-national datasets counted once)</p>
	<div id="chart-country" class="plotly-chart"></div>
	</div>

	<div class="chart-card tall">
	<h3>Top Datasets by Record Count (log scale)</h3>
	<p>Largest datasets ranked by number of records or segments</p>
	<div id="chart-records" class="plotly-chart"></div>
	</div>

	<div class="chart-card">
	<h3>Access Type by Lead Category</h3>
	<p>How open access varies across lead-count categories</p>
	<div id="chart-stacked" class="plotly-chart"></div>
	</div>

	<div class="chart-card">
	<h3>Sampling Frequency Distribution</h3>
	<p>How many datasets use each common sampling rate</p>
	<div id="chart-hz" class="plotly-chart"></div>
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	</div>
	</section>

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	{ name: 'Chapman-Shaoxing (Arrhythmia)', n: 45152 },
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	type: 'log', color: MUTED, gridcolor: BORDER,
	title: { text: 'Records (log scale)', font:{color:MUTED,size:11} },
	},
	yaxis: { color: TEXT, tickfont: { size: 10 }, automargin: true },
	}, config);

	/* ── 5. Stacked bar: Access by lead category ── */
	const categories = ['12-Lead (PhysioNet)', '12-Lead (Other)', '2-Lead', '1-Lead', '3-Lead', 'BSPM/ECGI'];
	const openCounts = [19, 11, 12, 9, 2, 1];
	const credCounts = [ 3, 1, 0, 0, 0, 0];
	const restCounts = [ 2, 3, 0, 1, 0, 0];
	Plotly.newPlot('chart-stacked', [
	{ name: 'Open', type: 'bar', x: categories, y: openCounts, marker:{color:GREEN},
	hovertemplate: '<b>%{x}</b><br>Open: %{y}<extra></extra>' },
	{ name: 'Credentialed', type: 'bar', x: categories, y: credCounts, marker:{color:AMBER},
	hovertemplate: '<b>%{x}</b><br>Credentialed: %{y}<extra></extra>' },
	{ name: 'Restricted', type: 'bar', x: categories, y: restCounts, marker:{color:RED},
	hovertemplate: '<b>%{x}</b><br>Restricted: %{y}<extra></extra>' },
	], {
	...layout_base,
	barmode: 'stack',
	margin: { t: 10, r: 16, b: 80, l: 40 },
	xaxis: { color: MUTED, tickangle: -20, tickfont:{size:11} },
	yaxis: { color: MUTED, gridcolor: BORDER, title:{text:'Datasets',font:{color:MUTED,size:11}} },
	legend: { ...layout_base.legend, orientation:'h', x:0.5, xanchor:'center', y:-0.25 },
	}, config);

	/* ── 6. Bar: Sampling frequency distribution ── */
	const hzLabels = ['100 Hz','125 Hz','128 Hz','200/250 Hz','257 Hz','300 Hz','360 Hz','400 Hz','500 Hz','977–1000 Hz','Mixed/Other'];
	const hzCounts = [2, 2, 3, 7, 2, 1, 3, 3, 23, 6, 12];
	Plotly.newPlot('chart-hz', [{
	type: 'bar',
	x: hzLabels,
	y: hzCounts,
	marker: {
	color: hzCounts,
	colorscale: [[0,'#2e3a6e'],[0.5,ACCENT2],[1,ACCENT]],
	showscale: false,
	},
	hovertemplate: '<b>%{x}</b><br>%{y} datasets<extra></extra>',
	text: hzCounts,
	textposition: 'outside',
	textfont: { color: MUTED, size: 11 },
	}], {
	...layout_base,
	showlegend: false,
	margin: { t: 10, r: 16, b: 90, l: 50 },
	xaxis: { color: MUTED, tickangle: -35, tickfont:{size:11} },
	yaxis: { color: MUTED, gridcolor: BORDER, title:{text:'Datasets',font:{color:MUTED,size:11}} },
	}, config);

	})();
	</script>

	<footer>
	<p>Maintained by <a href="https://github.com/vlbthambawita" target="_blank">Vajira Thambawita</a> · <a href="https://github.com/vlbthambawita/ECGDatasets" target="_blank">GitHub</a></p>
	</footer>

	<script>
	const searchInput = document.getElementById('search');
	const filterBtns = document.querySelectorAll('.filter-btn');
	const rows = document.querySelectorAll('#tbody tr, #tbody1 tr, #tbody2 tr, #tbody3 tr, #tbody4 tr, #tbody5 tr');
	const noResults = document.getElementById('no-results');

	let activeAccess = 'all';
	let activeLeads = 'all';

	function applyFilters() {
	const query = searchInput.value.toLowerCase();
	let visible = 0;

	rows.forEach(row => {
	const text = (row.dataset.text + ' ' + row.innerText).toLowerCase();
	const access = row.dataset.access;
	const leads = row.dataset.leads \|\| '12';

	const matchesSearch = !query \|\| text.includes(query);
	const matchesAccess =
	activeAccess === 'all' \|\|
	(activeAccess === 'open' && access === 'open') \|\|
	(activeAccess === 'credentialed' && access === 'credentialed') \|\|
	(activeAccess === 'restricted' && access === 'restricted');
	const matchesLeads = activeLeads === 'all' \|\| leads === activeLeads;

	if (matchesSearch && matchesAccess && matchesLeads) {
	row.classList.remove('hidden');
	visible++;
	} else {
	row.classList.add('hidden');
	}
	});

	noResults.style.display = visible === 0 ? 'block' : 'none';
	}

	searchInput.addEventListener('input', applyFilters);

	filterBtns.forEach(btn => {
	btn.addEventListener('click', () => {
	const group = btn.dataset.group;
	filterBtns.forEach(b => { if (b.dataset.group === group) b.classList.remove('active'); });
	btn.classList.add('active');
	if (group === 'access') activeAccess = btn.dataset.filter;
	if (group === 'leads') activeLeads = btn.dataset.filter;
	applyFilters();
	});
	});
	</script>

	<script>
	// Load version badge from _version.json written by CI at deploy time
	(function () {
	fetch('_version.json?_=' + Date.now())
	.then(function (r) { return r.ok ? r.json() : null; })
	.then(function (v) {
	if (!v) return;
	var badge = document.getElementById('version-badge');
	var tagEl = document.getElementById('vbadge-tag');
	var shaEl = document.getElementById('vbadge-sha');
	var dateEl = document.getElementById('vbadge-date');
	if (v.tag) {
	tagEl.textContent = v.tag;
	} else {
	tagEl.textContent = 'dev';
	}
	if (v.sha) shaEl.textContent = v.sha;
	if (v.date) {
	var d = new Date(v.date);
	dateEl.textContent = d.toISOString().slice(0, 10);
	}
	badge.style.display = 'flex';
	})
	.catch(function () { /* no _version.json in local dev — that's fine */ });
	})();
	</script>

	</body>
	</html>