Automated analysis of multi-channel EEG in preterm infants

[1]  Sabine Van Huffel,et al.  Line length as a robust method to detect high-activity events: Automated burst detection in premature EEG recordings , 2014, Clinical Neurophysiology.

[2]  Neil Marlow,et al.  Short term outcomes after extreme preterm birth in England: comparison of two birth cohorts in 1995 and 2006 (the EPICure studies) , 2012, BMJ : British Medical Journal.

[3]  Hiroyuki Kidokoro,et al.  EEG for Predicting Early Neurodevelopment in Preterm Infants: An Observational Cohort Study , 2012, Pediatrics.

[4]  Carola van Pul,et al.  Automatic burst detection for the EEG of the preterm infant. , 2011, Physiological measurement.

[5]  A. Furby,et al.  Prognostic value of EEG in very premature newborns , 2011, Archives of Disease in Childhood: Fetal and Neonatal Edition.

[6]  P. G. Larsson,et al.  Feasibility of Long-Term Continuous EEG Monitoring During the First Days of Life in Preterm Infants: An Automated Quantification of the EEG Activity , 2011, Pediatric Research.

[7]  Sampsa Vanhatalo,et al.  Optimization of an NLEO-based algorithm for automated detection of spontaneous activity transients in early preterm EEG , 2010, Physiological measurement.

[8]  S. Huffel,et al.  Automated neonatal seizure detection mimicking a human observer reading EEG , 2008, Clinical Neurophysiology.

[9]  Michel J. A. M. van Putten,et al.  The revised brain symmetry index , 2007, Clinical Neurophysiology.

[10]  M. Vecchierini,et al.  Normal EEG of premature infants born between 24 and 30 weeks gestational age: Terminology, definitions and maturation aspects , 2007, Neurophysiologie Clinique/Clinical Neurophysiology.

[11]  A. Yli-Hankala,et al.  Description of the Entropy™ algorithm as applied in the Datex‐Ohmeda S/5™ Entropy Module , 2004, Acta anaesthesiologica Scandinavica.

[12]  Tapio Seppänen,et al.  Automatic Analysis and Monitoring of Burst Suppression in Anesthesia , 2002, Journal of Clinical Monitoring and Computing.

[13]  M. Vecchierini,et al.  EEG patterns in 10 extreme premature neonates with normal neurological outcome: qualitative and quantitative data , 2003, Brain and Development.

[14]  A. Okumura,et al.  Background electroencephalographic (EEG) activities of very preterm infants born at less than 27 weeks gestation: a study on the degree of continuity , 2001, Archives of disease in childhood. Fetal and neonatal edition.

[15]  M. André,et al.  Normal EEG in very premature infants: reference criteria , 2000, Clinical Neurophysiology.

[16]  J. Frenzel,et al.  Brain dysmaturity index for automatic detection of high-risk infants. , 2000, Pediatric neurology.

[17]  J Gotman,et al.  Automatic EEG analysis during long-term monitoring in the ICU. , 1998, Electroencephalography and clinical neurophysiology.

[18]  J. Ménard,et al.  Prognostic value of neonatal electroencephalography in premature newborns less than 33 weeks of gestational age. , 1997, Electroencephalography and clinical neurophysiology.

[19]  G. Cioni,et al.  Electroencephalographic Dysmaturity in Preterm Infants: A Prognostic Tool in the Early Postnatal Period , 1996, Neuropediatrics.

[20]  G Cioni,et al.  Background EEG activity in preterm infants: correlation of outcome with selected maturational features. , 1994, Electroencephalography and clinical neurophysiology.

[21]  G. Holmes,et al.  Prognostic value of background patterns in the neonatal EEG. , 1993, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[22]  H. Monyer,et al.  Interburst interval measurements in the EEGs of premature infants with normal neurological outcome. , 1989, Electroencephalography and clinical neurophysiology.

[23]  T. Higuchi Approach to an irregular time series on the basis of the fractal theory , 1988 .

[24]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.