This database was created and contributed by Tatiana Lugovaya, who used it
in her master's thesis:
Lugovaya T.S. Biometric human identification based on electrocardiogram.
[Master's thesis] Faculty of Computing Technologies and Informatics,
Electrotechnical University "LETI", Saint-Petersburg, Russian Federation;
June 2005.
Read a brief summary of the thesis by its author.
Please cite this thesis 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/cgi/content/full/101/23/e215];
2000 (June 13).
The database contains 310 ECG recordings, obtained from 90 persons. Each
recording contains:
- ECG lead I, recorded for 20 seconds, digitized at 500 Hz with 12-bit
resolution over a nominal ±10 mV range;
- 10 annotated beats (unaudited R- and T-wave peaks annotations from an
automated detector);
- information (in the .hea file for the record) containing age,
gender and recording date.
The records were obtained from volunteers (44 men and 46 women aged from 13
to 75 years who were students, colleagues, and friends of the author). The
number of records for each person varies from 2 (collected during one day)
to 20 (collected periodically over 6 months).
The raw ECG signals are rather noisy and contain both high and low
frequency noise components. Each record includes both raw and filtered
signals:
- Signal 0: ECG I (raw signal)
- Signal 1: ECG I filtered (filtered signal)
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DOI 2015-09-21 13:00 19
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ANNOTATORS 2011-09-30 11:00 73 list of annotators
RECORDS 2011-09-30 11:01 4.9K list of record names
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biometric.shtml 2014-03-05 16:18 36K
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