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This database is described in
Greenwald SD.
Improved detection and classification of arrhythmias in noise-corrupted
electrocardiograms using contextual information.
Ph.D. thesis, Harvard-MIT Division of Health Sciences and Technology, 1990.
Please cite this publication when referencing this material, and also include the standard citation for PhysioNet:
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):e215-e220 [Circulation Electronic Pages;
http://circ.ahajournals.org/content/101/23/e215.full];
2000 (June 13).
This database includes 78 half-hour ECG recordings chosen to supplement the examples of supraventricular arrhythmias in the MIT-BIH Arrhythmia Database.