Epileptic Seizure Detection and Prevention

Low-power online seizure detection for implantable devices

Implantable high-accuracy, and low-power seizure detection is a challenge. However, different implantable devices have different goals (seizure monitoring, seizure early warning, or treatment), and pursuing a one-size-fits-all seizure detection/prediction algorithm may not be the most efficient to address the needs of these different applications. The purpose of this project is to develop seizure detection algorithms tailored for the needs of these different applications. Furthermore, we investigate how to combine different algorithms with different strengths to achieve a superior seizure detection performance while keeping the power and space requirements low.

Large-Amplitude Multi-Neuron Bursts Before Focal Neocortical EEG Seizure in Rats

Early Ictogenesis Detection (EID) aims to recognize cellular neurophysiological signals that develop about 1 minute before the onset of an EEG seizure. In this project, we investigate the phenomenon of abnormal/non-physiological multi-neuron bursts developing before the onsets of focal neocortical EEG seizures in freely-behaving rats. We show that abnormally large-amplitude multi-neuron bursts with patterns different from analogous electrical events during sleep and non-specific tissue irritation can be detected before EEG seizure onsets in at least some (“indicator”) recording channels in the neocortical seizure focus. The goal of this project is to specifically determine whether abnormal/non-physiological multi-neuron bursts develop within about 1 minute before the onsets of focal neocortical EEG seizures in freely-behaving rats and thus whether these bursts can potentially be used for seizure detection.

Selected Related Publications

  1. T. Kim, N. Sertac Artan, I. W. Selesnick, and H. J. Chao, “Seizure Detection Methods Using A Cascade Architecture For Real-Time Implantable Devices,” in 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013), Osaka, Japan, Jul. 2013. [ bib | pdf ]
  2. C.-L. Sha, T. Kim, N. Sertac Artan, and H. J. Chao, “Compression-Ratio-Based Seizure Detection,” in 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013), Osaka, Japan, Jul. 2013. [ bib | pdf ]
  3. N. Ludvig, H. M. Tang, N. Sertac Artan, P. Mirowski, G. Medveczky, S. L. Baptiste, S. Darisi, R. I. Kuzniecky, O. Devinsky, and J. A. French, “Transmeningeal Muscimol Can Prevent Focal EEG Seizures in the Rat Neocortex Without Stopping Multineuronal Activity in The Treated Area,” Brain Research, vol. 1385, pp. 182-191, Apr. 2011. [ bib ]
  4. N. Sertac Artan, P. Mirowski, H. Tang, G. Medveczky, S. Baptiste, H. J. Chao, O. Devinsky, R. Kuzniecky, and N. Ludvig, “Detecting Abnormally Large-Amplitude Multi-Neuron Bursts Before Focal Neocortical EEG Seizure Onset In Freely Behaving Rats,” Epilepsia, vol. 50, p. 391, Mar. 2009. [ bib ]
  5. N. Ludvig, H. Tang, S. Baptiste, G. Medveczky, N. Sertac Artan, H. J. Chao, P. Mirowski, O. Devinsky, J. French, and R. Kuzniecky, “Cellular Electrophysiological Effects of Seizure-Preventing Concentrations of Transmeningeal Muscimol in the Rat Neocortex,” Epilepsia, vol. 50, p. 390, 2009. [ bib ]