Literature DB >> 12691437

Long-term ST database: a reference for the development and evaluation of automated ischaemia detectors and for the study of the dynamics of myocardial ischaemia.

F Jager1, A Taddei, G B Moody, M Emdin, G Antolic, R Dorn, A Smrdel, C Marchesi, R G Mark.   

Abstract

The long-term ST database is the result of a multinational research effort. The goal was to develop a challenging and realistic research resource for development and evaluation of automated systems to detect transient ST segment changes in electrocardiograms and for supporting basic research into the mechanisms and dynamics of transient myocardial ischaemia. Twenty-four hour ambulatory ECG records were selected from routine clinical practice settings in the USA and Europe, between 1994 and 2000, on the basis of occurrence of ischaemic and non-ischaemic ST segment changes. Human expert annotators used newly developed annotation protocols and a specially developed interactive graphic editor tool (SEMIA) that supported paperless editing of annotations and facilitated international co-operation via the Internet. The database contains 86 two- and three-channel 24 h annotated ambulatory records from 80 patients and is stored on DVD-ROMs. The database annotation files contain ST segment annotations of transient ischaemic (1155) and heart-rate related ST episodes and annotations of non-ischaemic ST segment events related to postural changes and conduction abnormalities. The database is intended to complement the European Society of Cardiology ST-T database and the MIT-BIH and AHA arrhythmia databases. It provides a comprehensive representation of 'real-world' data, with numerous examples of transient ischaemic and non-ischaemic ST segment changes, arrhythmias, conduction abnormalities, axis shifts, noise and artifacts.

Entities:  

Keywords:  Non-programmatic

Mesh:

Year:  2003        PMID: 12691437     DOI: 10.1007/BF02344885

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   3.079


  12 in total

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Journal:  IEEE Trans Biomed Eng       Date:  2000-09       Impact factor: 4.538

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Review 3.  Electrocardiographic and signal monitoring in ischaemic heart disease: state of the art and perspective.

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Authors:  G E Dower; A Yakush; S B Nazzal; R V Jutzy; C E Ruiz
Journal:  J Electrocardiol       Date:  1988       Impact factor: 1.438

6.  Guidelines for ambulatory electrocardiography. A report of the American College of Cardiology/American Heart Association Task Force on Assessment of Diagnostic and Therapeutic Cardiovascular Procedures (Subcommittee on Ambulatory Electrocardiography).

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Journal:  J Am Coll Cardiol       Date:  1989-01       Impact factor: 24.094

7.  Imaging-documented cardiovascular signal database for assessing methods for ischaemia analysis.

Authors:  A Taddei; M Emdin; M Varanini; G Nassi; M Bertinelli; E Picano; C Marchesi
Journal:  J Med Eng Technol       Date:  1997 Sep-Oct

8.  Classification of arrhythmic events in ambulatory electrocardiogram, using artificial neural networks.

Authors:  R Silipo; M Gori; A Taddei; M Varanini; C Marchesi
Journal:  Comput Biomed Res       Date:  1995-08

9.  An adaptive backpropagation neural network for real-time ischemia episodes detection: development and performance analysis using the European ST-T database.

Authors:  N Maglaveras; T Stamkopoulos; C Pappas; M G Strintzis
Journal:  IEEE Trans Biomed Eng       Date:  1998-07       Impact factor: 4.538

10.  Long-term ST database: a reference for the development and evaluation of automated ischaemia detectors and for the study of the dynamics of myocardial ischaemia.

Authors:  F Jager; A Taddei; G B Moody; M Emdin; G Antolic; R Dorn; A Smrdel; C Marchesi; R G Mark
Journal:  Med Biol Eng Comput       Date:  2003-03       Impact factor: 3.079

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Journal:  J Med Syst       Date:  2018-01-11       Impact factor: 4.460

8.  Non-invasive computerised detection of acute coronary occlusion.

Authors:  G Dori; Y Denekamp; S Fishman; A Rosenthal; V Frajewicki; B S Lewis; H Bitterman
Journal:  Med Biol Eng Comput       Date:  2004-05       Impact factor: 2.602

9.  Classification of ischemic and non-ischemic cardiac events in Holter recordings based on the continuous wavelet transform.

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