CAN EEG PROCESSING REVEAL SEIZURE PREDICTION PATTERNS?

机译：脑电图可以显示揭示的预测模式吗？

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Epilepsy is characterized by an unexpected and frequent malfunction of the brain. Electrical activity in the brain has been studied for years in an attempt to predict seizures. This paper processes raw intracranial EEG recordings from different subjects in the time prior to seizure. A set of indicators is extracted from non-overlapping scrolling windows of 1 sec duration. The objective was to identify patterns that reveal that a seizure is developing before it occurs. While the exhaustive analysis did not detect patterns appropriate to predict a seizure, some indicators were observed to behave in time more similar independent of the subject. Similar time evolution was found for the activity and the power of the alpha and delta bands. It is also shown that the behavior of the correlation integral is somehow similar minutes before the seizure.

机译：癫痫病的特征是大脑出乎意料且频繁出故障。为了预测癫痫发作，对大脑中的电活动进行了多年研究。本文在癫痫发作之前的时间内处理来自不同受试者的原始颅内脑电图记录。从持续时间为1秒的非重叠滚动窗口中提取了一组指标。目的是在癫痫发作发生之前识别出显示发作的模式。尽管详尽的分析未检测到适合预测癫痫发作的模式，但观察到一些指标在时间上的行为更相似，而与受试者无关。对于α和δ带的活性和功效，发现了类似的时间演化。还显示了相关积分的行为在癫痫发作之前的几分钟内有点相似。

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来源
《IASTED(International Association of Science and Technology for Development) International Conference on Graphics and Visualization in Engineering; 20070103-05; Clearwater,FL(US)》|2007年|P.47-52|共6页
会议地点 ClearwaterFL(US)
作者
Maria T. Tito; Melvin Ayala; Ilker Yaylali; Mercedes Cabrerizo; Armando Barreto; Naphtali Rishe; Malek Adjouadi;
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作者单位

Department of Electrical and Computer Engineering, Florida International University 10555 W. Flagler Street, Miami FL 33174, U.S.A.;

Department of Neurology, Miami Children's Hospital 3100 South West 62nd Avenue, Miami, F1 33155, U. S. A.;

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原文格式 PDF
正文语种 eng
中图分类工程制图;
关键词
EEG; epilepsy; seizure prediction;

机译：脑电图;癫痫;癫痫发作预测;

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1. Prediction of rhythmic and periodic EEG patterns and seizures on continuous EEG with early epileptiform discharges [J] . Koren J., Herta J., Draschtak S., Epilepsy & behavior: E&B . 2015,第Null期

机译：有早期癫痫样放电的连续性脑电图的节律性和周期性脑电图预测和癫痫发作
2. Information theoretic measures of network coordination in high-frequency scalp EEG reveal dynamic patterns associated with seizure termination [J] . StamoulisC., SchomerD.L., ChangB.S. Epilepsy research . 2013,第3期

机译：高频头皮脑电图网络协调的信息理论方法揭示了癫痫发作终止的动态模式
3. Absence seizures: individual patterns revealed by EEG-fMRI. [J] . Moeller F, LeVan P, Muhle H, Epilepsia: Journal of the International League against Epilepsy . 2010,第10期

机译：失神发作：EEG-fMRI揭示的个别模式。
4. CAN EEG PROCESSING REVEAL SEIZURE PREDICTION PATTERNS? [C] . Maria T. Tito, Melvin Ayala, Ilker Yaylali, IASTED International Conference on Graphics and Visualization in Engineering . 2007

机译：EEG处理可以揭示癫痫发布预测模式吗？
5. Multi-Feature Analysis of Eeg Signal on Seizure Patterns and Deep Neural Structures for Prediction of Epileptic Seizures [D] . Ma, Xinyuan. 2020

机译：癫痫发作模式和深神经结构对癫痫癫痫发作预测的多种特征分析
6. Editorial commentary on special issue of Advances in EEG Signal Processing and Machine Learning for Epileptic Seizure Detection and Prediction [O] . Larbi Boubchir 2020

机译：关于癫痫发作检测和预测的脑电信号处理和机器学习进展专刊的社论评论
7. Seizure Prediction Based on Classification of EEG Synchronization Patterns with On-line Retraining and Post-Processing Scheme [O] . Cheng-yi Chiang, Nai-fu Chang, Tung-chien Chen, 2013

机译：基于在线再训练和后处理方案的脑电同步模式分类的癫痫发作预测

CAN EEG PROCESSING REVEAL SEIZURE PREDICTION PATTERNS?

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