Seizure detection in adult ICU patients based on changes in EEG synchronization likelihood

IntroductionSeizures are common in Intensive Care Unit (ICU) patients, and may increase neuronal injury.PurposeTo explore the possible value of synchronization likelihood (SL) for the automatic detection of seizures in adult ICU patients.MethodsWe included EEGs from ICU patients with a variety of diagnoses. The gold standard for further analyses was the consensus judgment of three clinical neurophysiologists who classified 150 scalp EEG epochs as “definitely epileptiform,” “definitely nonepileptiform,” or “uncertain.” SL estimates the statistical interdependencies between two time series, such as two EEG channels. We computed the average synchronization by calculating the SL between one channel and every other channel, and taking the mean of these values.ResultsThe mean SL in the 38 “definitely epileptiform” epochs ranged from 0.095 to 0.386 (mean 0.189; SD 0.066). In the 34 “definitely nonepileptiform” epochs the mean SL ranged from 0.087 to 0.158 (mean 0.115; SD 0.016; p<0.0005). The area under the ROC curve was 0.812 (95% Confidence Interval 0.725 to 0.898).ConclusionThe mean SL may distinguish between seizure and nonseizure epochs, and may prove helpful to monitor epileptic activity in ICU patients.

[1]  F. Takens.  Detecting strange attractors in turbulence , 1981 .

[2]  Theiler,et al.  Spurious dimension from correlation algorithms applied to limited time-series data. , 1986, Physical review. A, General physics.

[3]  F. Pierelli,et al.  Long-term EEG-video-audio monitoring: computer detection of focal EEG seizure patterns. , 1992, Electroencephalography and clinical neurophysiology.

[4]  K. Jordan,et al.  Neurophysiologic monitoring in the neuroscience intensive care unit. , 1995, Neurologic clinics.

[5]  L. Tsimring,et al.  Generalized synchronization of chaos in directionally coupled chaotic systems. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[6]  M. Salinsky.  A practical analysis of computer based seizure detection during continuous video-EEG monitoring. , 1997, Electroencephalography and clinical neurophysiology.

[7]  C. Elger,et al.  CAN EPILEPTIC SEIZURES BE PREDICTED? EVIDENCE FROM NONLINEAR TIME SERIES ANALYSIS OF BRAIN ELECTRICAL ACTIVITY , 1998 .

[8]  J. Martinerie,et al.  Epileptic seizures can be anticipated by non-linear analysis , 1998, Nature Medicine.

[9]  G. B. Young,et al.  Do nonconvulsive seizures damage the brain?--Yes. , 1998, Archives of neurology.

[10]  A J Gabor,et al.  Seizure detection using a self-organizing neural network: validation and comparison with other detection strategies. , 1998, Electroencephalography and clinical neurophysiology.

[11]  Joshua R. Smith,et al.  Prevalence of nonconvulsive status epilepticus in comatose patients , 2000, Neurology.

[12]  J. Martinerie,et al.  Anticipation of epileptic seizures from standard EEG recordings , 2001, The Lancet.

[13]  C. Stam,et al.  Synchronization likelihood: an unbiased measure of generalized synchronization in multivariate data sets , 2002 .

[14]  Cornelis J Stam,et al.  Seizure detection in the neonatal EEG with synchronization likelihood , 2003, Clinical Neurophysiology.

[15]  A. Schulze-Bonhage,et al.  How well can epileptic seizures be predicted? An evaluation of a nonlinear method. , 2003, Brain : a journal of neurology.

[16]  S. Huffel,et al.  Anticipation of epileptic seizures from standard EEG recordings , 2003, The Lancet.

[17]  Michael J. A. M. Van Putten,et al.  Nearest neighbor phase synchronization as a measure to detect seizure activity from scalp EEG recordings. , 2003 .

[18]  J. Martinerie,et al.  Anticipation of epileptic seizures from standard EEG recordings , 2003, The Lancet.

[19]  C J Stam,et al.  Neonatal Seizure Monitoring Using Non-Linear EEG Analysis , 2004, Neuropediatrics.

[20]  S. Mayer,et al.  Detection of electrographic seizures with continuous EEG monitoring in critically ill patients , 2004, Neurology.

[21]  Scott B. Wilson,et al.  Data Analysis for Continuous EEG Monitoring in the ICU: Seeing the Forest and the Trees , 2004, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[22]  F. H. Lopes da Silva,et al.  Nonlinear dynamics of epileptic seizures on basis of intracranial EEG recordings , 2005, Brain Topography.

[23]  J. Gotman,et al.  A system to detect the onset of epileptic seizures in scalp EEG , 2005, Clinical Neurophysiology.

[24]  C. Stam,et al.  Nonlinear dynamical analysis of EEG and MEG: Review of an emerging field , 2005, Clinical Neurophysiology.

[25]  V. Lagerburg,et al.  Detecting temporal lobe seizures from scalp EEG recordings: A comparison of various features , 2005, Clinical Neurophysiology.

[26]  Gordon Lightbody,et al.  An evaluation of automated neonatal seizure detection methods , 2005, Clinical Neurophysiology.

[27]  K. Lehnertz,et al.  The First International Collaborative Workshop on Seizure Prediction: summary and data description , 2005, Clinical Neurophysiology.