A Segmental Approach with SWT Technique for Denoising the EOG Signal. (10th November 2015)
- Record Type:
- Journal Article
- Title:
- A Segmental Approach with SWT Technique for Denoising the EOG Signal. (10th November 2015)
- Main Title:
- A Segmental Approach with SWT Technique for Denoising the EOG Signal
- Authors:
- Rajesh, Naga
- Other Names:
- Song Aiguo Academic Editor.
- Abstract:
- Abstract : The Electrooculogram (EOG) signal is often contaminated with artifacts and power-line while recording. It is very much essential to denoise the EOG signal for quality diagnosis. The present study deals with denoising of noisy EOG signals using Stationary Wavelet Transformation (SWT) technique by two different approaches, namely, increasing segments of the EOG signal and different equal segments of the EOG signal. For performing the segmental denoising analysis, an EOG signal is simulated and added with controlled noise powers of 5 dB, 10 dB, 15 dB, 20 dB, and 25 dB so as to obtain five different noisy EOG signals. The results obtained after denoising them are extremely encouraging. Root Mean Square Error (RMSE) values between reference EOG signal and EOG signals with noise powers of 5 dB, 10 dB, and 15 dB are very less when compared with 20 dB and 25 dB noise powers. The findings suggest that the SWT technique can be used to denoise the noisy EOG signal with optimum noise powers ranging from 5 dB to 15 dB. This technique might be useful in quality diagnosis of various neurological or eye disorders.
- Is Part Of:
- Modelling and simulation in engineering. Volume 2015(2015)
- Journal:
- Modelling and simulation in engineering
- Issue:
- Volume 2015(2015)
- Issue Display:
- Volume 2015, Issue 2015 (2015)
- Year:
- 2015
- Volume:
- 2015
- Issue:
- 2015
- Issue Sort Value:
- 2015-2015-2015-0000
- Page Start:
- Page End:
- Publication Date:
- 2015-11-10
- Subjects:
- Engineering -- Simulation methods -- Periodicals
Engineering -- Mathematical models -- Periodicals
620.004 - Journal URLs:
- https://www.hindawi.com/journals/mse/ ↗
- DOI:
- 10.1155/2015/612843 ↗
- Languages:
- English
- ISSNs:
- 1687-5591
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 10538.xml