Automated ECG Segmentation Using Piecewise Derivative Dynamic Time Warping
| Main Authors: | Ali Zifan, Sohrab Saberi, Mohammad Hassan Moradi, Farzad Towhidkhah |
|---|---|
| Format: | Article Journal |
| Bahasa: | eng |
| Terbitan: |
, 2007
|
| Online Access: |
https://zenodo.org/record/1333010 |
Daftar Isi:
- 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.