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Uncertainty through polynomial chaos in the EEG problem

Rob De Staelen UGent (2011) Proceedings of the World Congress on Engineering 2011. 3. p.2658-2662
abstract
A sensitivity and correlation analysis of EEG sensors influenced by uncertain conductivity is conducted. We assume a three layer spherical head model with different and random layer conductivities. This randomness is modeled by Polynomial Chaos (PC). On average, we observe the least influenced electrodes along the great longitudinal fissure. Also, sensors located closer to a dipole source, are of greater influence to a change in conductivity -- this is in agreement with previous research. The highly influenced sensors were on average located temporal. This was also the case in the correlation analysis, which was made possible by our approach with PC. Sensors in the temporal parts of the brain are highly correlated. Whereas the sensors in the occipital and lower frontal region, though they are close together, are not so highly correlated as in the temporal regions.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
Electroencephalography, Polynomial Chaos, Sensitivity analysis, Correlation analysis, Uncertain conductivity
in
Proceedings of the World Congress on Engineering 2011
volume
3
pages
2658 - 2662
publisher
Newswood Limited
place of publication
Hong Kong, China
conference name
World Congress on Engineering 2011 (WCE 2011)
conference location
London, UK
conference start
2011-07-06
conference end
2011-07-08
ISBN
9789881925152
language
English
UGent publication?
yes
classification
C1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1219351
handle
http://hdl.handle.net/1854/LU-1219351
date created
2011-05-08 17:13:43
date last changed
2017-01-02 09:52:26
@inproceedings{1219351,
  abstract     = {A sensitivity and correlation analysis of EEG sensors influenced by uncertain conductivity is conducted. We assume a three layer spherical head model with different and random layer conductivities. This randomness is modeled by Polynomial Chaos (PC). On average, we observe the least influenced electrodes along the great longitudinal fissure. Also, sensors located closer to a dipole source, are of greater influence to a change in conductivity -- this is in agreement with previous research. The highly influenced sensors were on average located temporal. This was also the case in the correlation analysis, which was made possible by our approach with PC. Sensors in the temporal parts of the brain are highly correlated. Whereas the sensors in the occipital and lower frontal region, though they are close together, are not so highly correlated as in the temporal regions.},
  author       = {De Staelen, Rob},
  booktitle    = {Proceedings of the World Congress on Engineering 2011},
  isbn         = {9789881925152},
  keyword      = {Electroencephalography,Polynomial Chaos,Sensitivity analysis,Correlation analysis,Uncertain conductivity},
  language     = {eng},
  location     = {London, UK},
  pages        = {2658--2662},
  publisher    = {Newswood Limited},
  title        = {Uncertainty through polynomial chaos in the EEG problem},
  volume       = {3},
  year         = {2011},
}

Chicago
De Staelen, Rob. 2011. “Uncertainty Through Polynomial Chaos in the EEG Problem.” In Proceedings of the World Congress on Engineering 2011, 3:2658–2662. Hong Kong, China: Newswood Limited.
APA
De Staelen, Rob. (2011). Uncertainty through polynomial chaos in the EEG problem. Proceedings of the World Congress on Engineering 2011 (Vol. 3, pp. 2658–2662). Presented at the World Congress on Engineering 2011 (WCE 2011), Hong Kong, China: Newswood Limited.
Vancouver
1.
De Staelen R. Uncertainty through polynomial chaos in the EEG problem. Proceedings of the World Congress on Engineering 2011. Hong Kong, China: Newswood Limited; 2011. p. 2658–62.
MLA
De Staelen, Rob. “Uncertainty Through Polynomial Chaos in the EEG Problem.” Proceedings of the World Congress on Engineering 2011. Vol. 3. Hong Kong, China: Newswood Limited, 2011. 2658–2662. Print.