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Use of electrographic seizures and interictal epileptiform discharges for improving performance in seizure prediction

机译:使用拍摄癫痫发作和嵌入性癫痫型放电来提高癫痫发作预测性能

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Electroencephalography (EEG) is an important tool in analyzing brain activity. EEG recording is effectively used for detection and prediction of electrophysiological abnormalities due to epilepsy. Epileptic seizure is a brain disorder which affects the patients acutely. Seizures are controllable with medication in 70% of the cases, however the rest may continue to have recurring epileptic seizures despite medications. Since seizures are unpredictable clinically, these patients will also live with perpetual anxiety about the onset of seizure, apart from being affected by the seizure consequences such as drowsiness, headache, vomiting, etc. The seizures can cause injury to the patients, and in some cases may even result in death. Seizure prediction can aid patients with disabling seizure by detecting the seizure precursors in advance and alerting the patients or their caregivers. If the seizure is predicted in advance it can be aborted by fast acting Anti-epileptic drugs (AEDs) or other treatment procedures. This will also aid pre-surgical video EEG monitoring wherein prediction of the ictal onset zone is paramount and machine alarms can be devised. In this paper, we are comparing the results of our research work related to the seizure prediction models. First model, as in usual practice, differentiates between preictal and interictal data segments only. The other seizure prediction model uses Interictal Epileptiform Discharges (IEDs), Electrographic Seizures (ES) and ictal data segments in addition to the first model. We found that the latter one provided better results and improved the seizure prediction performance.
机译:脑电图(EEG)是分析大脑活动的重要工具。由于癫痫,EEG记录有效地用于检测和预测电生理异常的电生理异常。癫痫癫痫发作是一种急剧影响患者的脑病。癫痫发作可在70%的病例中使用药物可控,但剩下的症状可能会继续患有药物的癫痫发作。由于缉获临床上是不可预测的,这些患者也将留住对癫痫发作的暂时的永久焦虑,除了受到癫痫发作,头痛,呕吐等的癫痫发作后果的影响,癫痫发作会对患者造成伤害,以及一些癫痫发作案件甚至可能导致死亡。癫痫发作预测可以通过预先检测癫痫发作前体检测癫痫发作前体并提醒患者或监护者来帮助患者。如果预先预测癫痫发作,则可以通过快速作用的抗癫痫药物(AED)或其他治疗方法来中止。这还将帮助预先手术视频EEG监测,其中ICTAL发作区域的预测是最重要的,并且可以设计机器警报。在本文中,我们正在比较我们的研究工作与癫痫发作预测模型相关的结果。首先模型,如通常的实践,仅区分预见和互墓数据段。除了第一模型之外,另一癫痫癫痫发作模型使用Interictal癫痫型放电(IED),拍摄癫痫发作和ICTAL数据段。我们发现后者提供了更好的结果并改善了癫痫发作预测性能。

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