Please use this identifier to cite or link to this item:
|Title:||Novel QRS detection by CWT for ECG sensor|
|Authors:||Zhang, F. |
|Source:||Zhang, F., Lian, Y. (2007). Novel QRS detection by CWT for ECG sensor. Conference Proceedings - IEEE Biomedical Circuits and Systems Conference Healthcare Technology, BiOCAS2007 : 211-214. ScholarBank@NUS Repository. https://doi.org/10.1109/BIOCAS.2007.4463346|
|Abstract:||Existing wavelet transform methods usually realize the QRS detection by sourcing for two modulus maxima with opposite sign and locating the zero crossing point between them at high decomposition scale. However high scale wavelet transform is often contaminated with severe baseline drift. In addition, common sense indicates that detecting zero crossing is not an easy task compared to the detection of maximum point. In this paper, a novel algorithm based on continuous wavelet transform (CWT) is proposed to accurately detect QRS. It employs a first-order derivative-based differentiator to suppress noise and baseline drift and uses high scale continuous wavelet transform to peak the zero crossing R point produced by differentiator to ease the task of QRS detection. It is shown by simulation that the proposed algorithm outperforms many existing methods and achieves an average detection rate of 99.69%, a sensitivity of 99.87%, and a positive prediction of 99.82% against the lead II of study records from the MIT-BIH Arrhythmia database. © 2007 IEEE.|
|Source Title:||Conference Proceedings - IEEE Biomedical Circuits and Systems Conference Healthcare Technology, BiOCAS2007|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 14, 2017
checked on Dec 10, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.