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Large Scale Arrhythmia Database (LSAD)

Overview

The large scale arrhythmia database (LSAD) is a large-scale, multi-center, multi-lead, and multi-class ECG dataset for arrhythmia detection. The dataset contains ECG recordings from 45,152 patients. The dataset is collected from 3 different centers: Shaoxing People's Hospital, the Second Affiliated Hospital of Zhejiang University, and the First Affiliated Hospital of Zhejiang University. The dataset contains 11 different arrhythmia classes and 1 normal class. The dataset is collected from 12-lead ECGs and is annotated by a team of expert cardiologists. The dataset includes over 100 scp codes.

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Usage

Example

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from pathlib import Path
import neuralspot_edge as nse
import heartkit as hk

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

# Download dataset
ds.download(force=False)

# Create signal generator
data_gen = self.ds.signal_generator(
    patient_generator=nse.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)

Statistics

Acronym Name Full Name Frequency, n(%) Age, Mean ± SD Male,n(%)
SB Sinus Bradycardia 15,528 (38.6) 58.4 ± 14.02 9844 (63.4%)
SR Sinus Rhythm 7,291 (18.1) 54.38 ± 16.17 4107 (56.33%)
AFIB Atrial Fibrillation 7,028 (17.5) 73.07 ± 11.27 4051 (57.64%)
ST Sinus Tachycardia 6,208 (15.4) 54.24 ± 21.41 3208 (51.68%)
AFL Atrial Flutter 1,725 (4.3) 71.57 ± 13.23 1001 (58.03%)
SI Sinus Irregularity 1,773 (4.4) 37.3 ± 22.98 979 (55.22%)
SVT Supraventricular Tachycardia 542 (1.3) 55.44 ± 18.41 289 (53.32%)
AT Atrial Tachycardia 133 (0.3) 65.92 ± 18.7 69 (51.88%)
AVNRT Atrioventricular Node Reentrant Tachycardia 16 (0.03) 57.88 ± 17.34 12 (75%)
AVRT Atrioventricular Reentrant Tachycardia 7 (0.01) 56.43 ± 17.89 5 (71.43%)
WAP Wandering Atrial Pacemaker 7 (0.01) 51.14 ± 31.83 6 (85.71%)

Funding

This dataset received funding from the Kay Family Foundation Data Analytic Grant. This dataset received funding from 2018 Shaoxing Medical and Hygiene Research Grant, ID 2018C30070.

License

The dataset is available under Creative Commons Attribution 4.0 International Public License