Automated Segmentation of ECG Signals using Piecewise Derivative Dynamic Time Warping

被引：0
|
作者：
Zifan, Ali [1 ]
Moradi, Mohammad Hassan [2 ]
Saberi, Sohrab [3 ]
Towhidkhah, Farzad [3 ]
机构：
[1] Amirkabir Univ Technol, Dept Biomed Engn, Neuromuscular Syst Lab, Tehran 158754413, Iran
[2] Amirkabir Univ Technol, Fac Biomed Engn, Biol Signal Proc Lab, Tehran 158754413, Iran
[3] Amirkabir Univ Technol, Dept Biomed Engn, Tehran 158754413, Iran
来源：
PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 14 | 2006年 / 14卷
关键词：
Adaptive Piecewise Constant Approximation; Dynamic programming; ECG segmentation; Piecewise Derivative Dynamic Time Warping;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Electrocardiogram (ECG) segmentation is necessary to help reduce the time consuming task of manually annotating ECG's. Several algorithms have been developed to segment the ECG automatically. We first review several of such methods, and then present a new single lead segmentation method based on Adaptive piecewise constant approximation (APCA) and Piecewise derivative dynamic time warping (PDDTW). The results are tested on the QT database. We compared our results to Laguna's two lead method. Our proposed approach has a comparable mean error, but yields a slightly higher standard deviation than Laguna's method.
引用
收藏
页码：301 / +
页数：2
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