@article{(Open Science Index):https://publications.waset.org/pdf/7002,
	  title     = {Automated ECG Segmentation Using Piecewise Derivative Dynamic Time Warping },
	  author    = {Ali Zifan and  Sohrab Saberi and  Mohammad Hassan Moradi 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 Medical and Health Sciences},
	  volume    = {1},
	  number    = {1},
	  year      = {2007},
	  pages     = {28 - 32},
	  ee        = {https://publications.waset.org/pdf/7002},
	  url   	= {https://publications.waset.org/vol/1},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 1, 2007},