McEvoy Robert P, Faul Stephen, Marnane William P
Department of Electrical & Electronic Engineering, University College Cork, Western Road, Ireland.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:2443-6. doi: 10.1109/IEMBS.2010.5626068.
REACT (Real-Time EEG Analysis for event deteCTion) is a Support Vector Machine based technology which, in recent years, has been successfully applied to the problem of automated seizure detection in both adults and neonates. This paper describes the implementation of REACT on a commercial DSP microprocessor; the Analog Devices Blackfin®. The primary aim of this work is to develop a prototype system for use in ambulatory or in-ward automated EEG analysis. Furthermore, the complexity of the various stages of the REACT algorithm on the Blackfin processor is analysed; in particular the EEG feature extraction stages. This hardware profile is used to select a reduced, platform-aware feature set, in order to evaluate the seizure classification accuracy of a lower-complexity, lower-power REACT system.
REACT(用于事件检测的实时脑电图分析)是一种基于支持向量机的技术,近年来已成功应用于成人和新生儿的癫痫自动检测问题。本文描述了REACT在一款商用DSP微处理器——模拟器件公司的Blackfin®上的实现。这项工作的主要目的是开发一个用于门诊或住院自动脑电图分析的原型系统。此外,还分析了Blackfin处理器上REACT算法各个阶段的复杂度;特别是脑电图特征提取阶段。利用此硬件配置文件来选择一个简化的、与平台相关的特征集,以便评估复杂度和功耗较低的REACT系统的癫痫分类准确率。