Methods Inf Med 2010; 49(05): 473-478
DOI: 10.3414/ME09-02-0041
Special Topic – Original Articles
Schattauer GmbH

Time Varying Neonatal Seizure Localization

W. Deburchgraeve
1   Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium
,
P. J. Cherian
2   Department of Clinical Neurophysiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
,
M. De Vos
1   Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium
,
R. M. Swarte
3   Department of Neonatology, Sophia Children’s Hospital, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
,
J. H. Blok
2   Department of Clinical Neurophysiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
,
G. H. Visser
2   Department of Clinical Neurophysiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
,
P. Govaert
3   Department of Neonatology, Sophia Children’s Hospital, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
,
S. Van Huffel
1   Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium
› Author Affiliations
Further Information

Publication History

received: 22 October 2009

accepted: 12 June 2009

Publication Date:
17 January 2018 (online)

Summary

Background: A common cause for damage to the neonatal brain is a shortage in the oxygen supply to the brain or asphyxia. Neonatal seizures are the most frequent manifestation of neonatal neurologic disorders. Multichannel EEG recordings allow topographic localization of seizure foci.

Objectives: We want to objectively determine the spatial distribution of the seizure on the scalp, the location in time and order the dominant sources in the brain based on their strength.

Methods: In this paper we combine a method based on higher order CP-decomposition with subsequent singular value decomposition (SVD).

Results: We illustrate the abilities of the method on simulated as well as on real neonatal seizure EEG.

Conclusions: The proposed method provides reliable time and spatial information about the seizure, gives a clear overview of what is going on in the EEG and allows easy interpretation.

 
  • References

  • 1 Volpe JJ. Neonatal seizures. Neurology of the newborn. 5th ed. Philadelphia: WB Saunders; 2008
  • 2 Hellstrom-Westas L, Rosen I, Swenningsen NW. Silent seizures in sick infants in early life. Diagnosis Methods Inf Med 5/2010 © Schattauer 2010
  • 3 Scher MS, Painter MJ, Bergman I, Barmada MA, Brunberg J. EEG diagnoses of neonatal seizures: clinical correlations and outcome. Pediatr Neurol 1985; 5: 17-24.
  • 4 Murray DM, Boylan GB, Ali I, Ryan CA, Murphy BP, Connolly S. Defining the gap between electro-graphic seizure burden, clinical expression and staff recognition of neonatal seizures. Arch Dis Child Fetal Neonatal 2008; 93: 187-191.
  • 5 Deburchgraeve W, Cherian PJ, De Vos M, Swarte RM, Blok JH, Visser GH, Govaert P, Van Huffel S. Automated neonatal seizure detection mimicking a human observer reading EEG. Clin Neurophysiol 2008; 119: 2447-2454.
  • 6 Deburchgraeve W, Cherian PJ, De Vos M, Swarte RM, Blok JH, Visser GH, Govaert P, Van Huffel S. Neonatal seizure localization using PARAFAC decomposition. Clin Neurophysiol 2009; 120: 1787-1796.
  • 7 Miwakeichi F, Martinez-Montes E, Valdés-Sosa PA, Nishiyama N, Mizuhara H, Yamaguchi Y. Decomposing EEG data into space-time-frequency components using parallel factor analysis. Neuroimage 2004; 22: 1035-1045.
  • 8 De Vos M, Vergult A, De Lathauwer L, De Clercq W, Van Huffel S, Dupont P, Palmini A, Van Paesschen W. Canonical decomposition of ictal scalp EEG reliably detects the seizure onset zone. NeuroImage 2007; 37: 844-854.
  • 9 Acar E, Aykut-Bingol C, Bingol H, Bro R, Yener B. Multiway analysis of epilepsy tensors. Bioinformatics 2007; 23: 10-18.
  • 10 Smilde A, Bro R, Geladi P. Multi-way Analysis with applications in the Chemical Sciences. John Wiley & Sons; 2004