MIMIC-III-Ext-PPG — ICU Wearable PPG Benchmark [Large-Scale, WFDB Format]
Catalog Summary
"Large-scale quality-assessed ICU PPG benchmark derived from MIMIC-III, with ECG, ABP, and respiration signals in 30-second WFDB segments. Multi-task format supporting cardiovascular and respiratory signal analysis for wearable algorithm development."
Catalog Notes
Overview
MIMIC-III-Ext-PPG is a curated, large-scale benchmark dataset derived from the MIMIC-III ICU database, specifically structured for photoplethysmography (PPG) research relevant to wearable health monitoring. It provides quality-assessed 30-second waveform segments including PPG, ECG, arterial blood pressure (ABP), and respiratory signals (RESP).
The dataset addresses a key gap in the wearable sensing research community: prior public PPG datasets were either small in scale or lacked support for multiple classification and regression tasks. MIMIC-III-Ext-PPG enables direct benchmarking of wearable-grade signal processing algorithms for tasks including arrhythmia detection, blood pressure estimation, respiratory rate estimation, and signal quality assessment.
Structured in the WFDB (WaveForm DataBase) format, it is directly compatible with PhysioNet's toolchain and major biomedical signal processing libraries in Python, MATLAB, and Julia.
Column Schema
| Column / Field | Description |
|---|---|
| PPG | Photoplethysmography waveform channel (primary signal). |
| ECG | Electrocardiogram waveform channel where available. |
| ABP | Arterial blood pressure waveform channel where available. |
| RESP | Respiratory signal channel where available. |
| segment_id | Identifier for each 30-second waveform segment. |
| patient_id | Anonymized ICU patient identifier. |
| quality_flag | Signal quality assessment label per segment. |
| metadata CSV | Rich set of metadata variables accompanying each record. |
Key Statistics
- Total Records: large-scale multi-patient ICU dataset (thousands of patients)
- Segment Length: 30 seconds per waveform segment
- Channels: PPG + ECG, ABP, RESP where available
- File Format: WFDB (compatible with Python wfdb, biosppy, neurokit2, MATLAB)
- Source: MIMIC-III clinical database
- Published: February 2026
Use Cases
- Wearable PPG algorithm development and benchmarking for cardiovascular monitoring
- Non-invasive blood pressure estimation from PPG signals
- Arrhythmia detection and respiratory rate estimation using wearable-grade signals
- Signal quality assessment model training for IoT health devices
Source & Attribution
MIMIC-III-Ext-PPG is hosted on PhysioNet and was developed to provide a high-quality, multi-task PPG benchmark for the wearable and digital health research community. It builds on the MIMIC-III clinical database from the MIT Laboratory for Computational Physiology.
View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on Other.
Preview on OtherCite This Dataset
The dataset creators ask users of this dataset to cite the accompanying paper. Use one of the verified formats below.
Moulaeifard, M., Charlton, P. H., & Strodthoff, N. (2026). MIMIC-III-Ext-PPG: A PPG Benchmark Dataset for Cardiorespiratory Analysis. PhysioNet. https://doi.org/10.13026/r6k1-xt76
Source metadata: Other (2026) · DOI: 10.13026/r6k1-xt76
Indexed by IoTDataset.com on Apr 10, 2026
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