Seizure prediction: Methods

被引:87
作者
Carney, Paul R. [1 ,2 ,3 ,4 ,5 ]
Myers, Stephen [1 ,2 ,3 ,4 ,5 ]
Geyer, James D. [6 ]
机构
[1] Univ Florida, Coll Med, Dept Pediat, Gainesville, FL 32610 USA
[2] Univ Florida, Coll Med, Dept Neurol, Gainesville, FL 32610 USA
[3] Univ Florida, Coll Med, Dept Neurosci, Gainesville, FL 32610 USA
[4] Univ Florida, Coll Med, Dept Biomed Engn, Gainesville, FL 32610 USA
[5] Univ Florida, Coll Med, Wilder Ctr Excellence Epilepsy Res, McKnight Brain Inst, Gainesville, FL 32610 USA
[6] Univ Alabama, Dept Neurol, Tuscaloosa, AL USA
关键词
Seizure prediction; Quantitative electroencephalographic analysis; Epilepsy; Seizures; Univariate methods; Multivariate methods; CEREBRAL-BLOOD-FLOW; EPILEPTIC SEIZURES; REAL-TIME; EEG; PREDICTABILITY; ANTICIPATION; ENERGY; ONSET;
D O I
10.1016/j.yebeh.2011.09.001
中图分类号
B84 [心理学]; C [社会科学总论]; Q98 [人类学];
学科分类号
03 ; 0303 ; 030303 ; 04 ; 0402 ;
摘要
Epilepsy, one of the most common neurological diseases, affects over 50 million people worldwide. Epilepsy can have a broad spectrum of debilitating medical and social consequences. Although antiepileptic drugs have helped treat millions of patients, roughly a third of all patients have seizures that are refractory to pharmacological intervention. The evolution of our understanding of this dynamic disease leads to new treatment possibilities. There is great interest in the development of devices that incorporate algorithms capable of detecting early onset of seizures or even predicting them hours before they occur. The lead time provided by these new technologies will allow for new types of interventional treatment. In the near future, seizures may be detected and aborted before physical manifestations begin. In this chapter we discuss the algorithms that make these devices possible and how they have been implemented to date. We also compare and contrast these measures, and review their individual strengths and weaknesses. Finally, we illustrate how these techniques can be combined in a closed-loop seizure prevention system. This article is part of a Supplemental Special Issue entitled The Future of Automated Seizure Detection and Prediction. (C) 2011 Elsevier Inc. All rights reserved.
引用
收藏
页码:S94 / S101
页数:8
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