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A Novel Method for Seizure Detection in Intracranial Eeg Recordings

机译:颅内EEG记录中癫痫发作检测的一种新方法

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Nearly 1 out of every 100 person on the planet is afflicted to Epilepsy, which is characterized by the occurrence of spontaneous seizures[8]. A victim maybe be given sufficiently high dose of anticonvulsant medication, in order to prevent seizures, but they may suffer from side effects. In 20-40% of cases with epilepsy, medication is not effective, even after surgical removal of brain tissues that cause epilepsy, many continue to still experience unprompted seizures. In spite of the fact that seizures occur sporadically, the patients suffer from persistent anxiety, due to possibility of a seizure occurring. The potential to help the patients in leading a more normal life can be done with the help of Seizure forecasting systems. If we are able to predict seizures as early as possible then we have the chance of effectively aborting the seizure using responsive neurostimulation. However if we fail to detect the seizure in its early stages then it becomes very hard to abort seizures. This model aims to create a suitable model to detect the seizure in its early stages so that proper actions can be taken.
机译:这个星球上每100人的近1个患者受到癫痫,其特征在于发生自发癫痫发作[8]。可能是受害者可以获得足够高剂量的抗惊厥药物,以防止癫痫发作,但它们可能患有副作用。在20-40%的癫痫病例中,药物治疗无效,即使在手术切除脑组织后导致癫痫,许多人继续仍然经历未突出的癫痫发作。尽管癫痫发作的刺激性发生了诸如刺激性的事实,由于发生癫痫发作的可能性,患者患有持续的焦虑。有助于帮助患者在缉获预测系统的帮助下可以采取更正常生活。如果我们能够尽早预测癫痫发作,那么我们有机会使用响应性神经刺激有效地中止癫痫发作。但是,如果我们未能在早期阶段检测癫痫发作,那么它变得非常难以中止癫痫发作。该模型旨在创建一个合适的模型来检测其早期阶段的癫痫发作,以便可以采取适当的行动。

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