Icentia11k Dataset

Overview

This dataset consists of ECG recordings from 11,000 patients and 2 billion labelled beats. The data was collected by the CardioSTAT, a single-lead heart monitor device from Icentia. The raw signals were recorded with a 16-bit resolution and sampled at 250 Hz with the CardioSTAT in a modified lead 1 position. We provide derived version of the dataset where each patient is stored in separate HDF5 files on S3. This makes it faster to download as well as makes it possible to leverage TensorFlow prefetch and interleave to parallelize data loading.

More info available on PhysioNet website

Usage

Python

from pathlib import Path
import helia_edge as helia
import heartkit as hk

ds = hk.DatasetFactory.get('icentia11k')(
    path=Path("./datasets/icentia11k")
)

# Download dataset
ds.download(force=False)

# Create signal generator
data_gen = self.ds.signal_generator(
    patient_generator=helia.utils.uniform_id_generator(ds.patient_ids, repeat=True, shuffle=True),
    frame_size=256,
    samples_per_patient=5,
    target_rate=100,
)

# Grab single ECG sample
ecg = next(data_gen)

Note

The Icentia11k dataset requires roughly 200 GB of disk space and can take around 2 hours to download.

Funding

This work is partially funded by a grant from Icentia, Fonds de Recherche en Santé du Québec, and the Institute of Data Valorization (IVADO).

Licensing

The Icentia11k dataset is available for non-commercial use only. Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License