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Detecting MMN in Infants EEG with Singular Value Decomposition

Sandberg, Johan LU ; Sandsten, Maria LU and Lindgren, Magnus LU (2005) 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. In 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005 p.4227-4230
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 USigmaVT = 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... (More)
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 USigmaVT = 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 (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005
pages
4227 - 4230
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005.
external identifiers
  • wos:000238998403228
  • scopus:33846933958
ISBN
0-7803-8741-4
DOI
10.1109/IEMBS.2005.1615397
language
English
LU publication?
yes
id
8fc3e1a3-08d6-460b-ae40-957327addf0e (old id 627399)
date added to LUP
2007-11-29 13:56:09
date last changed
2017-03-13 13:12:18
@inproceedings{8fc3e1a3-08d6-460b-ae40-957327addf0e,
  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 USigmaVT = 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},
  author       = {Sandberg, Johan and Sandsten, Maria and Lindgren, Magnus},
  booktitle    = {27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005},
  isbn         = {0-7803-8741-4},
  language     = {eng},
  pages        = {4227--4230},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Detecting MMN in Infants EEG with Singular Value Decomposition},
  url          = {http://dx.doi.org/10.1109/IEMBS.2005.1615397},
  year         = {2005},
}