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Denoising EOG Signal using Stationary Wavelet Transform Cover

Denoising EOG Signal using Stationary Wavelet Transform

Measurement Science Review
Volume 12 (2012): Issue 2 (April 2012)
By: Rajesh Naga,  S Chandralingam,  T Anjaneyulu and  K Satyanarayana  
Open Access
|Apr 2012

References

  1. Zhao Lv, Xiaoping Wu, Mi Li, Chao Zhang. (2008). Implementation of the EOG-based human computer interface system. In The 2nd International Conference on Bioinformatics and Biomedical Engineering (CBBE 2008), 16-18 May 2008, 2188-2191.10.1109/ICBBE.2008.877
    Search in Google Scholar
  2. Reddy, M. S, Narasimha, B., Suresh, E., Rao, K. S. (2010). Analysis of EOG signals using wavelet transform for detecting eye blinks. In International Conference on Wireless Communications and Signal Processing (WCSP), 21-23 October 2010, IEEE, 1-4.10.1109/WCSP.2010.5633797
    Search in Google Scholar
  3. Bulling, A., Ward, J. A., Gellersen, H., Troster, G. (2011). Eye movement analysis for activity recognition using electrooculography. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33 (4), 741-753.10.1109/TPAMI.2010.8620421675
    Search in Google Scholar
  4. Mali, R. D., Khadtare, M. S., Bombale, U. L. (2011). Removal of 50Hz PLI using discrete wavelet transform for quality diagnosis of biomedical ECG signal. International Journal of Computer Applications, 23 (7), 1-6.
    Search in Google Scholar
  5. Krishnaveni, V., Jayaraman, S., Aravind, S., Hariharasudhan, V., Ramadoss, K. (2006). Automatic identification and removal of ocular artifacts from EEG using wavelet transform. Measurement Science Review, 6 (4), 45-57.
    Search in Google Scholar
  6. Kania, M., Fereniec, M., Maniewski, R. (2007). Wavelet denoising for multi-lead high resolution ECG signals. Measurement Science Review, 7 (4), 30-33.
    Search in Google Scholar
  7. Senthil Kumar, P., Arumuganathan, R., Sivakumar, K., Vimal, C. (2009). An adaptive method to remove ocular artifacts from EEG signals using wavelet transform. Journal of Applied Sciences Research, 5 (7), 741-745.
    Search in Google Scholar
  8. Raj, V. N. P., Venkateswarlu, T. (2011). ECG signal denoising using undecimated wavelet transform. In 3rd International Conference on Electronics Computer Technology (ICECT), 8-10 April 2011, IEEE, 94-98.10.1109/ICECTECH.2011.5941808
    Search in Google Scholar
  9. Mohan Kumar, B., Vidhya Lavanya, R. (2011). Signal denoising with soft threshold by using Chui-Lian (CL) multiwavelet. International Journal of Electronics & Communication Technology, 2 (1), 38-42.
    Search in Google Scholar
  10. Rosas-Orea, M. C. E., Hernandez-Diaz, M., Alarcon-Aquino, V., Guerrero-Ojeda, L. G. (2005). A comparative simulation study of wavelet based denoising algorithms. In 15th International Conference on Electronics, Communications and Computers (CONIELECOMP 2005), 28 February - 02 March, 2005, 125-130.10.1109/CONIEL.2005.6
    Search in Google Scholar
  11. Núcleo de Engenharia Biomédica do Instituto Superior Técnico. (2009/10). Labs PDS20092010_materialExtra_eogSig.mat.http://nebm.ist.utl.pt/repositorio/ficheiros/1750
    Search in Google Scholar
DOI: https://doi.org/10.2478/v10048-012-0010-0 | Journal eISSN: 1335-8871
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Language: English
Page range: 46 - 51
Published on: Apr 19, 2012
Published by: Slovak Academy of Sciences, Institute of Measurement Science
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
EOG signal,
Wavelet transform,
denoising,
thresholding,
biorthogonal wavelet
Related subjects:
Engineering,
Electrical engineering,
Control engineering, metrology and testing

© 2012 Rajesh Naga, S Chandralingam, T Anjaneyulu, K Satyanarayana, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons License.

Volume 12 (2012): Issue 2 (April 2012)