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).