@article{(Open Science Index):https://publications.waset.org/pdf/8423,
	  title     = {Automated Segmentation of ECG Signals using Piecewise Derivative Dynamic Time Warping},
	  author    = {Ali Zifan and  Mohammad Hassan Moradi and  Sohrab Saberi and  Farzad Towhidkhah},
	  country	= {},
	  institution	= {},
	  abstract     = {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.},
	    journal   = {International Journal of Biomedical and Biological Engineering},
	  volume    = {2},
	  number    = {8},
	  year      = {2008},
	  pages     = {182 - 185},
	  ee        = {https://publications.waset.org/pdf/8423},
	  url   	= {https://publications.waset.org/vol/20},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 20, 2008},