NDLI: Comparison of median filter and discrete dyadic wavelet transform for noise cancellation in electrocardiogram

Content Provider	IEEE Xplore Digital Library
Author	Wan-hua Lin Wong, M.Y. Li-na Pu Yuan-ting Zhang
Copyright Year	2010
Description	Author affiliation: Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055, China (Wan-hua Lin; Li-na Pu) \|\| Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China (Yuan-ting Zhang) \|\| Joint Research Centre for Biomedical Engineering, Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong (Wong, M.Y.)
Abstract	Development of noise cancellation algorithm is essential to facilitate accurate detection of electrocardiogram (ECG) in mobile health and wearable medical devices. In this study, we captured ECG from 20 subjects when they were at rest and during routine activities. The motion artifact in ECG was filtered using two non-linear filters: median filter and discrete dyadic wavelet transform. Signal-to-noise ratio (SNR) and computation time of the filters were determined. We found that median filter showed larger SNR (7.61±1.21 dB) than discrete dyadic wavelet transform did (5.35±1.34 dB). Conversely, discrete dyadic wavelet transform benefited to its short computation time. The algorithms of these non-linear filters should be further investigated to achieve both high SNR and fast computation in wearable and mobile monitoring systems.
Starting Page	2395
Ending Page	2398
File Size	368402
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5627195
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electrocardiography Finite impulse response filter Discrete wavelet transforms Signal to noise ratio
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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