Li, Tianning and Wen, Peng 
ORCID: https://orcid.org/0000-0003-0939-9145 and Jayamaha, Sophie
(2014)
Anaesthetic EEG signal denoise using improved nonlocal mean methods.
Australasian Physical and Engineering Sciences in Medicine, 37 (2).
pp. 431-437.
ISSN 0158-9938
Abstract
This paper applies the nonlocal mean (NLM) method to denoise the simulated and real electroencephalograph
signals. As a patch-based method, the NLM method calculates the weighted sum of a patch. The weight of each point is determined by the similarity between the points of the own patch and its neighbor. Based on the weighted sum, the noise is filtered out. In this study, the NLM denoising method is applied to signals with additive Gaussian white noise, spiking noise and specific frequency noise and the results are compared with that of the popular sym8 and db16 Wavelet threshold denoising (WTD) methods. The outcomes show that the NLM on average achieves 2.70 dB increase in improved signal to noise ratio (SNRimp) and 0.37 % drop in improved percentage distortion ratio compared with WTD. The moving adaptive shape patches-NLM performs better than the original NLM when the signals change dramatically. In addition, the performance of combined NLMWTD denoising method is also better than original WTD method (0.50–4.89 dB
higher in SNRimp), especially, when the signal quality is
poor.
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| Item Type: | Article (Commonwealth Reporting Category C) |
|---|---|
| Refereed: | Yes |
| Item Status: | Live Archive |
| Additional Information: | © 2014 Australasian College of Physical Scientists and Engineers in Medicine. Published version deposited in accordance with the copyright policy of the publisher. |
| Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences (1 Jul 2013 - 5 Sep 2019) |
| Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences (1 Jul 2013 - 5 Sep 2019) |
| Date Deposited: | 02 Jul 2014 01:46 |
| Last Modified: | 04 Jul 2016 05:16 |
| Uncontrolled Keywords: | denoising; EEG; moving adaptive shape patches; nonlocal mean method |
| Fields of Research (2008): | 09 Engineering > 0906 Electrical and Electronic Engineering > 090609 Signal Processing 09 Engineering > 0903 Biomedical Engineering > 090399 Biomedical Engineering not elsewhere classified 09 Engineering > 0903 Biomedical Engineering > 090303 Biomedical Instrumentation |
| Fields of Research (2020): | 40 ENGINEERING > 4006 Communications engineering > 400607 Signal processing 40 ENGINEERING > 4003 Biomedical engineering > 400399 Biomedical engineering not elsewhere classified 40 ENGINEERING > 4003 Biomedical engineering > 400305 Biomedical instrumentation |
| Socio-Economic Objectives (2008): | E Expanding Knowledge > 97 Expanding Knowledge > 970111 Expanding Knowledge in the Medical and Health Sciences |
| Identification Number or DOI: | https://doi.org/10.1007/s13246-014-0263-z |
| URI: | http://eprints.usq.edu.au/id/eprint/25369 |
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