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Uncertainty through polynomial chaos in the EEG problem

Rob De Staelen (UGent)
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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.
Keywords
Electroencephalography, Polynomial Chaos, Sensitivity analysis, Correlation analysis, Uncertain conductivity

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Citation

Please use this url to cite or link to this publication:

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.
@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},
}