Ali Zifan and Mohammad Hassan Moradi and Sohrab Saberi and Farzad Towhidkhah
Automated Segmentation of ECG Signals using Piecewise Derivative Dynamic Time Warping
182 - 185
2008
2
8
International Journal of Biomedical and Biological Engineering
https://publications.waset.org/pdf/8423
https://publications.waset.org/vol/20
World Academy of Science, Engineering and Technology
Electrocardiogram (ECG) segmentation is necessary
to help reduce the time consuming task of manually annotating
ECGs. 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 Lagunas two lead method. Our
proposed approach has a comparable mean error, but yields a slightly
higher standard deviation than Lagunas method.
Open Science Index 20, 2008