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Brain-computer interface for the epileptic seizures prediction and prevention
- Source :
- Proceedings 2020 8th International Winter Conference on Brain-Computer Interface (BCI), 1-5. Red Hook, NY : Curran, STARTPAGE=1;ENDPAGE=5;TITLE=Proceedings 2020 8th International Winter Conference on Brain-Computer Interface (BCI), Proceedings 2020 8th International Winter Conference on Brain-Computer Interface (BCI), pp. 1-5
- Publication Year :
- 2020
-
Abstract
- Contains fulltext : 217713.pdf (Publisher’s version ) (Closed access) 30% of epileptic patients are resistant to drug therapy. A prospective treatment strategy for refractory epilepsy patients is a brain-computer interface (BCI) in which the epileptic seizures are modulated either by the preprogrammed stimulation schedules (open loop) or via the closed-loop stimulation. The closed-loop BCI implies that seizures are automatically detected and that the detection triggers stimulation which subsequently aborts seizures. Up to now, this experimental treatment is only able to reduce seizures duration, while the ultimate aim is their complete abolishment. We have developed a closed-loop BCI aimed to predict and prevent spike-wave discharges, the electrophysiological anchor of absence seizures, in a genetic absence rat model; it predicted 45% of the seizures while the remaining ones were detected. When we evaluated the combination of the prediction and seizure detection with closed-loop electrical stimulation, a 72% decrease of seizure activity duration was achieved. The 8th International Winter Conference on Brain-Computer Interface (BCI) (Gangwon, Korea (South), 26-28 Feb. 2020)
Details
- Database :
- OpenAIRE
- Journal :
- Proceedings 2020 8th International Winter Conference on Brain-Computer Interface (BCI), 1-5. Red Hook, NY : Curran, STARTPAGE=1;ENDPAGE=5;TITLE=Proceedings 2020 8th International Winter Conference on Brain-Computer Interface (BCI), Proceedings 2020 8th International Winter Conference on Brain-Computer Interface (BCI), pp. 1-5
- Accession number :
- edsair.doi.dedup.....3d05e4dd503a0472e9672fe63a456444