10.6084/m9.figshare.5601652.v1
Paweł Pławiak
Paweł
Pławiak
ECG signals (1000 fragments)
figshare
2017
ECG
Biomedical signal processing and analysis
Classification
Machine learning
Feature extraction and selection
Health Informatics
Biomedical Engineering not elsewhere classified
Expert Systems
Knowledge Representation and Machine Learning
Pattern Recognition and Data Mining
2017-11-14 23:24:39
Dataset
https://figshare.com/articles/dataset/ECG_signals_1000_fragments_/5601652
For research purposes, the ECG signals were obtained from the PhysioNet service (http://www.physionet.org) from the MIT-BIH Arrhythmia database. The created database with ECG signals is described below. 1) The ECG signals were from 45 patients: 19 female (age: 23-89) and 26 male (age: 32-89). 2) The ECG signals contained 17 classes: normal sinus rhythm, pacemaker rhythm, and 15 types of cardiac dysfunctions (for each of which at least 10 signal fragments were collected). 3) All ECG signals were recorded at a sampling frequency of 360 [Hz] and a gain of 200 [adu / mV]. 4) For the analysis, 1000, 10-second (3600 samples) fragments of the ECG signal (not overlapping) were randomly selected. 5) Only signals derived from one lead, the MLII, were used. 6) Data are in mat format (Matlab).