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Real-time epileptic seizure detection on intra-cranial rat data using reservoir computing

Pieter Buteneers (UGent) , Benjamin Schrauwen (UGent) , David Verstraeten (UGent) and Dirk Stroobandt (UGent)
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Abstract
In this paper it is shown that Reservoir Computing can be successfully applied to perform real-time detection of epileptic seizures in Electroencephalograms (EEGs). Absence and tonic-clonic seizures are detected on intracranial EEG coming from rats. This resulted in an area under the Receiver Operating Characteristics (ROC) curve of about 0.99 on the data that was used. For absences an average detection delay of 0.3s was noted, for tonic-clonic seizures this was 1.5s. Since it was possible to process 15h of data on an average computer in 14.5 minutes all conditions are met for a fast and reliable real-time detection system.

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Chicago
Buteneers, Pieter, Benjamin Schrauwen, David Verstraeten, and Dirk Stroobandt. 2009. “Real-time Epileptic Seizure Detection on Intra-cranial Rat Data Using Reservoir Computing.” In Lecture Notes in Computer Science, ed. Mario Köppen, Nikola Kasabov, and George Coghill, 5506:56–63. Berlin, Germany: Springer.
APA
Buteneers, P., Schrauwen, B., Verstraeten, D., & Stroobandt, D. (2009). Real-time epileptic seizure detection on intra-cranial rat data using reservoir computing. In M. Köppen, N. Kasabov, & G. Coghill (Eds.), LECTURE NOTES IN COMPUTER SCIENCE (Vol. 5506, pp. 56–63). Presented at the 15th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Assembly (ICONIP 2008), Berlin, Germany: Springer.
Vancouver
1.
Buteneers P, Schrauwen B, Verstraeten D, Stroobandt D. Real-time epileptic seizure detection on intra-cranial rat data using reservoir computing. In: Köppen M, Kasabov N, Coghill G, editors. LECTURE NOTES IN COMPUTER SCIENCE. Berlin, Germany: Springer; 2009. p. 56–63.
MLA
Buteneers, Pieter, Benjamin Schrauwen, David Verstraeten, et al. “Real-time Epileptic Seizure Detection on Intra-cranial Rat Data Using Reservoir Computing.” Lecture Notes in Computer Science. Ed. Mario Köppen, Nikola Kasabov, & George Coghill. Vol. 5506. Berlin, Germany: Springer, 2009. 56–63. Print.
@inproceedings{721867,
  abstract     = {In this paper it is shown that Reservoir Computing can be successfully applied to perform real-time detection of epileptic seizures in Electroencephalograms (EEGs). Absence and tonic-clonic seizures are detected on intracranial EEG coming from rats. This resulted in an area under the Receiver Operating Characteristics (ROC) curve of about 0.99 on the data that was used. For absences an average detection delay of 0.3s was noted, for tonic-clonic seizures this was 1.5s. Since it was possible to process 15h of data on an average computer in 14.5 minutes all conditions are met for a fast and reliable real-time detection system.},
  author       = {Buteneers, Pieter and Schrauwen, Benjamin and Verstraeten, David and Stroobandt, Dirk},
  booktitle    = {LECTURE NOTES IN COMPUTER SCIENCE},
  editor       = {K{\"o}ppen, Mario and Kasabov, Nikola and Coghill, George},
  isbn         = {978-3-642-02489-4},
  issn         = {1611-3349},
  language     = {eng},
  location     = {Auckland, New Zealand},
  pages        = {56--63},
  publisher    = {Springer},
  title        = {Real-time epileptic seizure detection on intra-cranial rat data using reservoir computing},
  url          = {http://dx.doi.org/10.1007/978-3-642-02490-0\_7},
  volume       = {5506},
  year         = {2009},
}

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