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Heartbeat Signal Classification Dataset

Public Health & Epidemiology

Related Searches

ECG

Heartbeat Classification

Arrhythmia

Signal Processing

Time Series Classification

Medical Data

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Heartbeat Signal Classification Dataset Dataset on Opendatabay data marketplace

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About

Segmented and Preprocessed ECG Signals for Heartbeat Classification

Dataset Features

List and describe each column or key feature of the dataset.
  • ECG Signal: A sequence of values representing the electrocardiogram signal for a heartbeat. Each value corresponds to the amplitude of the signal at a given point in time.
  • Class Label: The classification label indicating the type of heartbeat. The categories include:
    • N: Normal heartbeat (0)
    • S: Supraventricular premature beat (1)
    • V: Premature ventricular contraction (2)
    • F: Fusion of ventricular and normal beat (3)
    • Q: Unclassified heartbeat (4)

Distribution

Detail the format, size, and structure of the dataset.
  • Data Volume:
    • 109,446 samples from the MIT-BIH Arrhythmia Dataset, 5 categories.
    • 14,552 samples from the PTB Diagnostic ECG Database, 2 categories.
    • 125Hz sampling frequency for both datasets.
    • Each sample is cropped, downsampled, and padded to a fixed size of 188 data points.

Usage

This dataset is ideal for a variety of applications:
  • Heartbeat Classification: Identifying different types of heartbeats, such as normal or arrhythmic conditions.
  • Medical Diagnosis: Assisting in detecting conditions like arrhythmias and myocardial infarction using machine learning models.

Coverage

Explain the scope and coverage of the dataset:
  • Geographic Coverage: Global (derived from international ECG databases).
  • Time Range: The data represents historical ECG records without a specific time range (general ECG patterns over time).
  • Demographics (if applicable): The dataset includes data from diverse populations with various heart conditions, such as normal heart rhythms, arrhythmias, and myocardial infarction.

License

CC0

Who Can Use It

List examples of intended users and their use cases:
  • Data Scientists: For training machine learning models, especially deep neural networks, for heartbeat classification.
  • Researchers: For conducting studies on heart disease and arrhythmia detection.
  • Medical Professionals: To enhance diagnostic tools that classify heartbeats and predict heart diseases.
This dataset is segmented and preprocessed, making it ideal for use in the development of machine learning models focused on heartbeat classification. The dataset has been used in research exploring the power of deep learning and transfer learning in ECG analysis.

Dataset Information

VIEWS

8

DOWNLOADS

1

LICENSE

CUSTOM

REGION

GLOBAL

UDQSSQUALITY

5 / 5

VERSION

1.0

Free