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Content Provider | IET Digital Library |
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Author | Ghosh, Rajdeep Sinha, Nidul Biswas, Saroj Kumar |
Abstract | Electroencephalogram (EEG) is a highly sensitive instrument and is frequently corrupted with eye blinks. Methods based on adaptive noise cancellation (ANC) and discrete wavelet transform (DWT) have been used as a standard technique for removal of eye blink artefacts. However, these methods often require visual inspection and appropriate thresholding for identifying and removing artefactual components from the EEG signal. The proposed work describes an automated windowed method with a window size of 0.45 s that is slid forward and fed to a support vector machine (SVM) classifier for identification of artefacts, after the identification of artefacts, it is fed to an autoencoder for correction of artefacts. The proposed method is evaluated on the data collected from the project entitled ‘Analysis of Brain Waves and Development of Intelligent Model for Silent Speech Recognition’. From the results it is observed that the proposed method performs better in identifying and removing artefactual components from EEG data than existing wavelet and ANC based methods. The proposed method does not require the application of independent component analysis (ICA) before processing and can be applied to multiple channels in parallel. |
Starting Page | 141 |
Ending Page | 148 |
Page Count | 8 |
ISSN | 17519675 |
Volume Number | 13 |
e-ISSN | 17519683 |
Issue Number | Issue 2, Apr (2019) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-spr/13/2 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2018.5111 |
Journal | IET Signal Processing |
Publisher Date | 2018-08-30 |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Adaptive Noise Cancellation Autoencoder Automated Eye Blink Artefact Removal Automated Windowed Method Bioelectric Signal Biology And Medical Computing Computer Vision And Image Processing Technique Digital Signal Processing Discrete Wavelet Transform EEG Data EEG Signal Electrical Activity in Neurophysiological Processes Electrodiagnostics And Other Electrical Measurement Technique Electroencephalogram Electroencephalography Eye Highly Sensitive Instrument Integral Transforms Knowledge Engineering Technique Medical Signal Processing Physiological Optics Physiological Vision Signal Classification Signal Denoising Signal Processing And Detection Support Vector Machine Visual Inspection |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Electrical and Electronic Engineering |
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