Literature DB >> 19779602

The PhysioNet / Computers in Cardiology Challenge 2008: T-Wave Alternans.

Gb Moody1.   

Abstract

The 9th annual PhysioNet/Computers in Cardiology challenge invited participants to measure T-wave alternans (TWA) in a set of 100 two-minute electrocardiograms that included subjects with a variety of risk factors for sudden cardiac death (including ventricular tachyarrhythmias, transient myocardial ischemia, and acute myocardial infarctions), healthy controls, and synthetic ECGs with calibrated amounts of artificial TWA. The participants' TWA estimates were used to develop a ranking of the 100 test cases in order of TWA content, and the Kendall rank correlation coefficient between this reference ranking and each individual participant's ranking of the 100 cases was calculated as a score (between -1 and 1; actual scores were between 0.11 and 0.92). The challenge yielded insights into the strengths and weaknesses of classic and novel TWA analyses, open-source implementations of a variety of methods, and a set of freely available ECGs with reference rankings of TWA content.

Entities:  

Year:  2008        PMID: 19779602      PMCID: PMC2749698          DOI: 10.1109/CIC.2008.4749089

Source DB:  PubMed          Journal:  Comput Cardiol        ISSN: 0276-6574


  4 in total

1.  PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.

Authors:  A L Goldberger; L A Amaral; L Glass; J M Hausdorff; P C Ivanov; R G Mark; J E Mietus; G B Moody; C K Peng; H E Stanley
Journal:  Circulation       Date:  2000-06-13       Impact factor: 29.690

2.  An Artificial Multi-Channel Model for Generating Abnormal Electrocardiographic Rhythms.

Authors:  Gd Clifford; S Nemati; R Sameni
Journal:  Comput Cardiol       Date:  2008

3.  Methodological principles of T wave alternans analysis: a unified framework.

Authors:  Juan Pablo Martínez; Salvador Olmos
Journal:  IEEE Trans Biomed Eng       Date:  2005-04       Impact factor: 4.538

Review 4.  Pathophysiological basis and clinical application of T-wave alternans.

Authors:  Antonis A Armoundas; Gordon F Tomaselli; Hans D Esperer
Journal:  J Am Coll Cardiol       Date:  2002-07-17       Impact factor: 24.094

  4 in total
  12 in total

1.  An Artificial Multi-Channel Model for Generating Abnormal Electrocardiographic Rhythms.

Authors:  Gd Clifford; S Nemati; R Sameni
Journal:  Comput Cardiol       Date:  2008

2.  A unified procedure for detecting, quantifying, and validating electrocardiogram T-wave alternans.

Authors:  H Naseri; H Pourkhajeh; M R Homaeinezhad
Journal:  Med Biol Eng Comput       Date:  2013-05-22       Impact factor: 2.602

3.  CSE database: extended annotations and new recommendations for ECG software testing.

Authors:  Radovan Smíšek; Lucie Maršánová; Andrea Němcová; Martin Vítek; Jiří Kozumplík; Marie Nováková
Journal:  Med Biol Eng Comput       Date:  2016-12-31       Impact factor: 2.602

4.  An artificial vector model for generating abnormal electrocardiographic rhythms.

Authors:  Gari D Clifford; Shamim Nemati; Reza Sameni
Journal:  Physiol Meas       Date:  2010-03-22       Impact factor: 2.833

5.  An Open-Source Standard T-Wave Alternans Detector for Benchmarking.

Authors:  A Khaustov; S Nemati; Gd Clifford
Journal:  Comput Cardiol       Date:  2008-09-14

6.  Heartbeats Do Not Make Good Pseudo-Random Number Generators: An Analysis of the Randomness of Inter-Pulse Intervals.

Authors:  Lara Ortiz-Martin; Pablo Picazo-Sanchez; Pedro Peris-Lopez; Juan Tapiador
Journal:  Entropy (Basel)       Date:  2018-01-30       Impact factor: 2.524

7.  Fast QRS detection with an optimized knowledge-based method: evaluation on 11 standard ECG databases.

Authors:  Mohamed Elgendi
Journal:  PLoS One       Date:  2013-09-16       Impact factor: 3.240

8.  A time-domain hybrid analysis method for detecting and quantifying T-wave alternans.

Authors:  Xiangkui Wan; Kanghui Yan; Linlin Zhang; Yanjun Zeng
Journal:  Comput Math Methods Med       Date:  2014-04-03       Impact factor: 2.238

9.  TERMA Framework for Biomedical Signal Analysis: An Economic-Inspired Approach.

Authors:  Mohamed Elgendi
Journal:  Biosensors (Basel)       Date:  2016-11-02

10.  Low Resource Complexity R-peak Detection Based on Triangle Template Matching and Moving Average Filter.

Authors:  Tam Nguyen; Xiaoli Qin; Anh Dinh; Francis Bui
Journal:  Sensors (Basel)       Date:  2019-09-16       Impact factor: 3.576

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