一种用于基准测试的开源标准T波交替检测算法。
An Open-Source Standard T-Wave Alternans Detector for Benchmarking.
作者信息
Khaustov A, Nemati S, Clifford Gd
机构信息
Institute of Cardiological Technics (Incart), St. Petersburg, Russia.
出版信息
Comput Cardiol. 2008 Sep 14;2008:509-512. doi: 10.1109/CIC.2008.4749090.
Abstract
We describe an open source algorithm suite for T-Wave Alternans (TWA) detection and quantification. The software consists of Matlab implementations of the widely used Spectral Method and Modified Moving Average with libraries to read both WFDB and ASCII data under windows and Linux. The software suite can run in both batch mode and with a provided graphical user interface to aid waveform exploration. Our software suite was calibrated using an open source TWA model, described in a partner paper [1] by Clifford and Sameni. For the PhysioNet/CinC Challenge 2008 we obtained a score of 0.881 for the Spectral Method and 0.400 for the MMA method. However, our objective was not to provide the best TWA detector, but rather a basis for detailed discussion of algorithms.
摘要
我们描述了一种用于检测和量化T波交替（TWA）的开源算法套件。该软件由广泛使用的频谱法和修正移动平均法的Matlab实现组成，并带有在Windows和Linux下读取WFDB和ASCII数据的库。该软件套件既可以批处理模式运行，也可以通过提供的图形用户界面来辅助波形探索。我们的软件套件使用了由Clifford和Sameni在一篇合作论文[1]中描述的开源TWA模型进行校准。在2008年生理网/计算机化心电挑战赛中，我们的频谱法得分0.881，修正移动平均法得分0.400。然而，我们的目标不是提供最佳的TWA检测器，而是为算法的详细讨论提供一个基础。
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本文引用的文献
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2
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3
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IEEE Trans Biomed Eng. 2005 Apr;52(4):599-613. doi: 10.1109/TBME.2005.844025.
4
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Circulation. 2000 Jun 13;101(23):E215-20. doi: 10.1161/01.cir.101.23.e215.
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