ECG5000
OpenML dataset with id 44793
Bradley Efron, Trevor Hastie, Iain Johnstone and Robert Tibshirani, Luis Ferreira
Full work available at URL: https://api.openml.org/data/v1/download/22111555/ECG5000.arff
Upload date: 19 November 2022
Dataset Characteristics
Number of classes: 0
Number of features: 141 (numeric: 141, symbolic: 0 and in total binary: 0 )
Number of instances: 4,998
Number of instances with missing values: 0
Number of missing values: 0
The original dataset for 'ECG5000' is a 20-hour long ECG downloaded from Physionet. The name is BIDMC Congestive Heart Failure Database(chfdb) and it is record 'chf07'. It was originally published in 'Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE. PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation 101(23)'. The data was pre-processed in two steps: (1) extract each heartbeat, (2) make each heartbeat equal length using interpolation. This dataset was originally used in paper 'A general framework for never-ending learning from time series streams', DAMI 29(6). After that, 5,000 heartbeats were randomly selected. The patient has severe congestive heart failure and the class values were obtained by automated annotation.
This page was built for dataset: ECG5000
