The Long-Term ST Database: A Research Resource for Algorithm
Development and Physiologic Studies of Transient Myocardial Ischemia

F Jager$^{1,2}$, A Taddei$^{3}$, M Emdin$^{3}$, G Antolic$^{4}$, R Dorn$^{1}$, GB Moody$^{2,5}$, B Glavic$^{1}$, A Smrdel$^{1}$,
M Varanini$^{3}$, M Zabukovec$^{1}$, S Bordigiago$^{3}$, C Marchesi$^{3}$, RG Mark$^{2,5}$

$^{1}$Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia
$^{2}$Harvard-M.I.T. Division of Health Sciences and Technology, Cambridge, MA, USA
$^{3}$CNR Institute of Clinical Physiology, Pisa, Italy
$^{4}$Department of Cardiology, University Medical Center, Ljubljana, Slovenia
$^{5}$Cardiology Division, Beth Israel Deaconess Medical Center, Boston, MA, USA

This article originally appeared in Computers in Cardiology 2000, vol. 27 (Piscataway, NJ: IEEE Computer Society Press). Please cite this publication when referencing this material. This HTML version incorporates minor revisions for publication on PhysioNet.

Abstract:

We present the Long Term ST Database, a collection of eighty 24-hour two and three lead ECG records from ambulatory subjects with transient ST segment abnormalities. The database provides a comprehensive standard research resource for quantitatively assessing the performance of automated detectors of transient ischemia, and for supporting basic research into the mechanisms and dynamics of transient ischemia. Records of the database contain annotated significant transient ischemic ST episodes, non-ischemic ST episodes caused by heart-rate related changes, non-ischemic ST events due to axis shifts or QRS conduction changes, and individual QRS and rhythm annotations, all made by human experts.

Samples of the Long-Term ST Database are available here.