Artifact reduction in multichannel pervasive EEG using hybrid WPT-ICA and WPT-EMD signal decomposition techniques
Artifact reduction in multichannel pervasive EEG using hybrid WPT-ICA and WPT-EMD signal decomposition techniques
In order to reduce the muscle artifacts in multi-channel pervasive Electroencephalogram (EEG) signals, we here propose and compare two hybrid algorithms by combining the concept of wavelet packet transform (WPT), empirical mode decomposition (EMD) and Independent Component Analysis (ICA). The signal cleaning performances of WPT-EMD and WPT-ICA algorithms have been compared using a signal-to-noise ratio (SNR)-like criterion for artifacts. The algorithms have been tested on multiple trials of four different artifact cases viz. eye-blinking and muscle artifacts including left and right hand movement and head-shaking.
artifact reduction, EMD, ICA, muscle artifact, pervasive EEG, wavelet packet transform
5864- 5868
Bono, Valentina
1cb487d9-7af0-421b-8207-a0e785e0c9dd
Jamal, Wasifa
3f70176e-843e-46b7-8447-4eefaef104f1
Das, Saptarshi
e06f2eb0-1e3e-453c-ba78-82eed18ceac9
Maharatna, Koushik
93bef0a2-e011-4622-8c56-5447da4cd5dd
4 May 2014
Bono, Valentina
1cb487d9-7af0-421b-8207-a0e785e0c9dd
Jamal, Wasifa
3f70176e-843e-46b7-8447-4eefaef104f1
Das, Saptarshi
e06f2eb0-1e3e-453c-ba78-82eed18ceac9
Maharatna, Koushik
93bef0a2-e011-4622-8c56-5447da4cd5dd
Bono, Valentina, Jamal, Wasifa, Das, Saptarshi and Maharatna, Koushik
(2014)
Artifact reduction in multichannel pervasive EEG using hybrid WPT-ICA and WPT-EMD signal decomposition techniques.
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on, Florence, Italy.
04 - 09 May 2014.
.
(doi:10.1109/ICASSP.2014.6854728).
Record type:
Conference or Workshop Item
(Paper)
Abstract
In order to reduce the muscle artifacts in multi-channel pervasive Electroencephalogram (EEG) signals, we here propose and compare two hybrid algorithms by combining the concept of wavelet packet transform (WPT), empirical mode decomposition (EMD) and Independent Component Analysis (ICA). The signal cleaning performances of WPT-EMD and WPT-ICA algorithms have been compared using a signal-to-noise ratio (SNR)-like criterion for artifacts. The algorithms have been tested on multiple trials of four different artifact cases viz. eye-blinking and muscle artifacts including left and right hand movement and head-shaking.
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Published date: 4 May 2014
Venue - Dates:
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on, Florence, Italy, 2014-05-04 - 2014-05-09
Keywords:
artifact reduction, EMD, ICA, muscle artifact, pervasive EEG, wavelet packet transform
Organisations:
Electronic & Software Systems
Identifiers
Local EPrints ID: 365058
URI: http://eprints.soton.ac.uk/id/eprint/365058
PURE UUID: a2fac7de-2319-4fde-a494-851558936ec5
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Date deposited: 20 May 2014 14:02
Last modified: 14 Mar 2024 16:45
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Contributors
Author:
Valentina Bono
Author:
Wasifa Jamal
Author:
Saptarshi Das
Author:
Koushik Maharatna
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