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Detecting MMN in Infants EEG with Singular Value Decomposition.

Sandberg, Johan LU ; Hansson, M and Lindgren, Magnus LU (2005) 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society In [Publication information missing]
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conference name
27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
conference dates
2005-09-01 - 2005-09-04
external identifiers
  • wos:000238998403228
  • scopus:33846933958
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English
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yes
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Abstract: Mismatch Negativity (MMN) is an EEG voltage fluctuation caused by the brain’s automatic reaction to unexpected changes in a repetitive stimulation. In an experiment we studied 68 infants of which 2/3 were born preterm. Due to noise of large amplitude, the MMN is difficult to detect in a single infant’s EEG. Therefore grand average, which is a average of many subjects EEG recordings, is sometimes used. In this paper Singular Value Decomposition (SVD) is proposed as an alternative to grand average. Consider the SVD USV2= M, where the rows of M contains noisy EEG epochs. Usually data is projected onto the leftmost column of V since this column represent the largest common component of the rows of M. When data is affected by noise of a very large amplitude we may need to choose another column of V. In this paper we propose to choose the leftmost column of V such that the elements of the corresponding column of U has approximately equal values.
id
51b282b9-3082-4211-893a-46c478fa6c40 (old id 925522)
date added to LUP
2016-04-04 11:55:27
date last changed
2020-01-12 21:31:15
@misc{51b282b9-3082-4211-893a-46c478fa6c40,
  author       = {Sandberg, Johan and Hansson, M and Lindgren, Magnus},
  language     = {eng},
  note         = {Conference Abstract},
  series       = {[Publication information missing]},
  title        = {Detecting MMN in Infants EEG with Singular Value Decomposition.},
  year         = {2005},
}