Development of an interhemispheric symmetry measurement in the neonatal brain

ICPRAM 2014 - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods

Volumn , Issue , 2014, Pages 765-770

  Koolen, Ninah ^a   Dereymaeker, Anneleen ^b   Jansen, Katrien ^b   Vervisch, Jan ^b   Matic, Vladimir ^a   De Vos, Maarten ^a,c   Naulaers, Gunnar ^b   Van Huffel, Sabine ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b UNIVERSITY HOSPITALS LEUVEN   (Belgium)

^c UNIVERSITY OF OLDENBURG   (Germany)

Author keywords

Channel symmetry index; Classification; EEG; One class svm; Preterm brain; Spectral power; Symmetry

Indexed keywords

BRAIN; CLASSIFICATION (OF INFORMATION); CRYSTAL SYMMETRY; ELECTROENCEPHALOGRAPHY; INTENSIVE CARE UNITS; SPECTRAL DENSITY; SUPPORT VECTOR MACHINES;

AUTOMATED ANALYSIS; BRAIN REGIONS; CHANNEL SYMMETRY; EEG SIGNALS; NEONATAL INTENSIVE CARE UNITS; NEURONAL DYSFUNCTION; ONE CLASS-SVM; SPECTRAL POWER;

PATTERN RECOGNITION;

EID: 84902308099     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5220/0004922407650770     Document Type: Conference Paper

References (19)

1. Cawley, G. C., 2006. Leave-One-Out Cross-Validation Based Model Selection Criteria for Weighted LSSVMs. In IJCNN, IEEE: p. 1661-1668.
2. Chih-Chung Chang and Chih-Jen Lin, LIBSVM : A library for support vector machines. In ACM Transactions on Intelligent Systems and Technology, 2: 27:1-27:27, 2011. Software available at http://www.csie.ntu.edu.tw/cjlin/libsvm.
3. Fourie, C., van Niekerk, A., Mucina, L., 2011. Optimising a one-class SVM for geographic object based novelty detection. In Proceedings of the first AfricaGeo conference. Cape Town, South Africa: p. 1-25.
4. Hayashi-Kurahashi, N., Kidokoro, H., Kubota, T. et al., 2012. EEG for predicting early neurodevelopment in preterm infants: An observational cohort study. In Pediatrics, 130: p.891-897.
5. Hellström-Westas, L., Klette, H., Thorngren-Jerneck, K., et al., 2001. Early prediction of outcome with aEEG in preterm infants with large intraventricular hemorrhages. In Neuropediatrics, 32: p. 319-324.
6. Hellström-Westas, L. and Rosén, I., 2005. Electroencephalography and brain damage in preterm infants. In Early Human Development, 81: p. 255-261.
7. Holmes, G. and Lombroso, T., 1993. Prognostic value of background Patterns in the neonatal EEG. In Journal of Clinical Neurophysiology, p. 323-352.
8. Hunyadi, B., De Vos, M., Signoretto, M., et al., 2011. Automatic Seizure Detection Incorporating Structural Information. In Artificial Neural Networks and Machine Learning-ICANN, 6791: p. 233-240.
9. Hunyadi, B., De Vos, M., Van Paesschen, W., et al., 2010. A mimicking approach for human epileptic seizure detection. In Proc. of the International Biosignal Processing Conference. Berlin, Germany: p. 1-4.
10. Koolen, N., Jansen, K., Vervisch, J., et al., 2013. Automatic burst detection based on line length in the premature EEG. In Proc. of the 6th International Conference on bio-inspired systems and signal processing (BIOSIGNALS). Barcelona, Spain: p. 105- 111.
11. Le Bihannic, A., Beauvais, K., Busnel, A., et al., 2012. Prognostic value of EEG in very premature newborns. In Arch Dis Child Fetal Neonatal, 97: p.106-109.
12. Okumura, A., Hayakawa, F., Kato, T., et al., 2002. Developmental outcome and types of chronic-stage EEG abnormalities in preterm infants. In Developmental Medicine and Child Neurology, 44: p. 729-734.
13. Palmu, K., Wikström, S., Hippeläinen, E., et al., 2010. Detection of 'EEG bursts' in the early preterm EEG: Visual vs. automated detection. In Clinical Neurophysiology, 121: p. 1015-1022.
14. Schölkopf, B., Smola, A. J., Williamson, R. C., et al., 2000. New Support Vector Algorithms. In Neural Computation, 12: p. 1207-1245.
15. Schölkopf, B., Platt, J.C., Shawe-Taylor, J., et al., 2001. Estimating the Support of a High-Dimensional Distribution. In Neural Computation, 13: p. 1443- 1471.
16. Smyser, C. D., Inder, T. E., Shimony, J.S., et al., 2010. Longitudinal analysis of neural network development in preterm infants. In Cerebral cortex, 20: p. 2852- 2862.
17. Vanhatalo, S. and Kaila, K., 2006. Development of neonatal EEG activity: from phenomenology to physiology. In Seminars in fetal & neonatal medicine, 11: p. 471-478.
18. Van Putten, M. and Tavy, D., 2004. Continuous Quantitative EEG Monitoring in Hemispheric Stroke Patients Using the Brain Symmetry index. In Stroke, 35: p. 2489-2492.
19. Vecchierini, M. F., André, M., d'Allest, A. M., et al., 2007. Normal EEG of premature infants born between 24 and 30 weeks gestational age: Terminology definitions and maturation aspects. In Clinical Neurophysiology, 37: p.311-323.