Real time eye blink noise removal from EEG signals using morphological component analysis
Real time eye blink noise removal from EEG signals using morphological component analysis
This paper presents a method of removing the noise caused by eye blinks from an electroencephalogram (EEG) signal in real time based on morphological component analysis (MCA). This method sparsely represents both the eye blink and the EEG signal basis matrices using a Short Time Fourier Transform (STFT). This approach has two main advantages: 1) fast computation of the estimation of the signal coefficients using the basis pursuit algorithm 2) less memory requirement. The obtained result shows that the correlation coefficient between the raw EEG and the cleaned EEG is between 0.72 and 0.94 which implies that it is possible to remove eye blink noise from the EEG signal in real time without affecting an underlying brain signal.
Matiko, Joseph W.
21477818-ba95-4fd6-beb9-8f81a27a46a4
Beeby, Stephen
ba565001-2812-4300-89f1-fe5a437ecb0d
Tudor, John
46eea408-2246-4aa0-8b44-86169ed601ff
4 June 2013
Matiko, Joseph W.
21477818-ba95-4fd6-beb9-8f81a27a46a4
Beeby, Stephen
ba565001-2812-4300-89f1-fe5a437ecb0d
Tudor, John
46eea408-2246-4aa0-8b44-86169ed601ff
Matiko, Joseph W., Beeby, Stephen and Tudor, John
(2013)
Real time eye blink noise removal from EEG signals using morphological component analysis.
35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’13), Osaka, Japan.
03 - 07 Jul 2013.
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper presents a method of removing the noise caused by eye blinks from an electroencephalogram (EEG) signal in real time based on morphological component analysis (MCA). This method sparsely represents both the eye blink and the EEG signal basis matrices using a Short Time Fourier Transform (STFT). This approach has two main advantages: 1) fast computation of the estimation of the signal coefficients using the basis pursuit algorithm 2) less memory requirement. The obtained result shows that the correlation coefficient between the raw EEG and the cleaned EEG is between 0.72 and 0.94 which implies that it is possible to remove eye blink noise from the EEG signal in real time without affecting an underlying brain signal.
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Published date: 4 June 2013
Venue - Dates:
35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’13), Osaka, Japan, 2013-07-03 - 2013-07-07
Organisations:
Electronics & Computer Science
Identifiers
Local EPrints ID: 358670
URI: http://eprints.soton.ac.uk/id/eprint/358670
PURE UUID: 2592f4a9-8901-44de-8182-f55cb9ae8b22
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Date deposited: 17 Oct 2013 12:08
Last modified: 15 Mar 2024 02:46
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Contributors
Author:
Joseph W. Matiko
Author:
Stephen Beeby
Author:
John Tudor
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