MIMIC-III-Ext-PPG, a PPG-based Benchmark Dataset for Cardiovascular and Respiratory Signal Analysis

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Authors: Mohammad Moulaeifard, Marie Kutscher, Philip J. Aston, Peter H. Charlton, Nils Strodthoff
Cited by: 1
References: 22

Abstract

We present MIMIC-III-Ext-PPG, a large-scale, quality-assessed photoplethysmography (PPG) dataset derived from the matched waveform subset of MIMIC-III. Our dataset provides 30-second PPG segments with annotations tailored for various cardiovascular and respiratory analyses. In particular, with 6.3 million segments from 6,189 subjects, it represents the largest publicly available resource for heart rhythm classification, with heart rhythm annotations derived from bedside charted observations. For subsets where arterial blood pressure (ABP), respiratory (RESP), and/or electrocardiography (ECG) signals are available, we also provide systolic/diastolic blood pressure, respiratory rate, and heart rate annotations, extracted using best practice from the underlying signals. We provide signal quality assessments for all signals. This ensures a high-quality, publicly available dataset of unprecedented size that can be used as a benchmarking resource for machine learning approaches for a broad range of prediction tasks, which remains easily extendable by leveraging additional clinical metadata from the MIMIC-III clinical database.

Fields of Study & Subjects

Non-Invasive Vital Sign Monitoring Heart Rate Variability and Autonomic Control ECG Monitoring and Analysis

Publication details

Journal / source
Scientific Data
Publisher
Springer Science and Business Media LLC
Volume
13
Issue
1
Publication date
28 April 2026
Language
EN