Suppr超能文献

复杂部分性发作的计算机化癫痫发作检测

Computerized seizure detection of complex partial seizures.

作者信息

Murro A M, King D W, Smith J R, Gallagher B B, Flanigin H F, Meador K

机构信息

Department of Neurology, VA Medical Center, Augusta, GA 30912.

出版信息

Electroencephalogr Clin Neurophysiol. 1991 Oct;79(4):330-3. doi: 10.1016/0013-4694(91)90128-q.

Abstract

In this study, we describe a computerized method that uses 3 quantified EEG features and discriminant analysis to automatically detect seizure EEG. The quantified EEG features were relative amplitude, dominant frequency and rhythmicity. Using EEGs recorded from intracranial electrodes, the seizure detection method was applied to consecutive non-overlapping 2-channel EEG epochs. A seizure detection sensitivity, ranging from 90% to 100%, was associated with a false positive detection rate of 1.5-2.5/h. The performance of the seizure detection method remained stable for EEG recorded over variable time periods.

摘要

在本研究中,我们描述了一种计算机化方法,该方法使用3种量化脑电图特征和判别分析来自动检测癫痫脑电图。量化脑电图特征为相对振幅、主导频率和节律性。利用颅内电极记录的脑电图,将癫痫检测方法应用于连续的、不重叠的双通道脑电图片段。癫痫检测灵敏度在90%至100%之间,假阳性检测率为每小时1.5 - 2.5次。癫痫检测方法的性能在不同时间段记录的脑电图中保持稳定。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验