Detection of seizure precursors from depth-EEG using a sign periodogram transform

Brief bursts of focal, low amplitude rhythmic activity have been observed on depth electroencephalogram (EEG) in the minutes before electrographic onset of seizures in human mesial temporal lobe epilepsy. We have found these periods to contain discrete, individualized synchronized activity in patient-specific frequency bands ranging from 20 to 40 Hz. We present a method for detecting and displaying these events using a periodogram of the sign-limited temporal derivative of the EEG signal, denoted joint sign periodogram event characterization transform (JSPECT). When applied to continuous 2-6 day depth-EEG recordings from ten patients with temporal lobe epilepsy, JSPECT demonstrated that these patient-specific EEG events reliably occurred 5-80 s prior to electrical onset of seizures in five patients with focal, unilateral seizure onsets. JSPECT did not reveal this type of activity prior to seizures in five other patients with bilateral, extratemporal or more diffuse seizure onsets on EEG. Patient-specific, localized rhythmic events may play an important role in seizure generation in temporal lobe epilepsy. The JSPECT method efficiently detects these events, and may be useful as part of an automated system for predicting electrical seizure onset in appropriate patients.

[1]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[2]  F W Sharbrough,et al.  Characterization and Comparison of Local Onset and Remote Propagated Electrographic Seizures Recorded with Intracranial Electrodes , 1998, Epilepsia.

[3]  K Lehnertz,et al.  Non-linear time series analysis of intracranial EEG recordings in patients with epilepsy--an overview. , 1999, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[4]  D. Colella,et al.  Brain chirps: spectrographic signatures of epileptic seizures , 2000, Clinical Neurophysiology.

[5]  J. S. Barlow,et al.  Methods of Analysis of Nonstationary EEGs, with Emphasis on Segmentation Techniques: A Comparative Review , 1985, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[6]  F. Wendling,et al.  Time-frequency matching of warped depth-EEG seizure observations , 1999, IEEE Transactions on Biomedical Engineering.

[7]  P H Crandall,et al.  Ictal localization of temporal lobe seizures with scalp/sphenoidal recordings , 1989, Neurology.

[8]  S. Kay.  Fundamentals of statistical signal processing: estimation theory , 1993 .

[9]  A J Gabor,et al.  Automated seizure detection using a self-organizing neural network. , 1996, Electroencephalography and clinical neurophysiology.

[10]  J. J. Niederhauser.  Simple electric model for epilepsy (SEMEY) , 2002 .

[11]  Piotr J. Franaszczuk,et al.  An autoregressive method for the measurement of synchronization of interictal and ictal EEG signals , 1999, Biological Cybernetics.

[12]  Brian Litt,et al.  Epileptic Seizures May Begin Clinical Study Hours in Advance of Clinical Onset: A Report of Five Patients , 2001 .

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

[14]  H G Wieser,et al.  Presurgical Evaluation: Current Role of Invasive EEG , 2000, Epilepsia.

[15]  L D Iasemidis,et al.  Non-linearity in invasive EEG recordings from patients with temporal lobe epilepsy. , 1997, Electroencephalography and clinical neurophysiology.

[16]  R. Fisher,et al.  High-frequency EEG activity at the start of seizures. , 1992, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

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

[18]  S. Spencer,et al.  Morphological Patterns of Seizures Recorded Intracranially , 1992, Epilepsia.

[19]  Saleem A. Kassam,et al.  Nonparametric detection : theory and applications , 1980 .

[20]  D. Spencer,et al.  The localizing value of depth electroencephalography in 32 patients with refractory epilepsy , 1982, Annals of neurology.

[21]  Steven G. Johnson,et al.  FFTW: an adaptive software architecture for the FFT , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[22]  J. Sackellares,et al.  Time dependencies in the occurrences of epileptic seizures , 1994, Epilepsy Research.

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

[24]  G. Vachtsevanos,et al.  Epileptic Seizures May Begin Hours in Advance of Clinical Onset A Report of Five Patients , 2001, Neuron.

[25]  Jan-Olof Gustavsson.  Detection in Non-Gaussian Noise , 1993 .

[26]  I. Osorio,et al.  Real‐Time Automated Detection and Quantitative Analysis of Seizures and Short‐Term Prediction of Clinical Onset , 1998, Epilepsia.

[27]  J. Gotman,et al.  A patient-specific algorithm for the detection of seizure onset in long-term EEG monitoring: possible use as a warning device , 1997, IEEE Transactions on Biomedical Engineering.