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使用四种基于位置的技术检测闭眼后阿尔法脑电图起始。

Detection of alpha electro-encephalogram onset following eye closure using four location-based techniques.

作者信息

Searle A, Kirkup L

机构信息

Department of Applied Physics, University of Technology, Sydney, Australia.

出版信息

Med Biol Eng Comput. 2001 Jul;39(4):434-40. doi: 10.1007/BF02345365.

Abstract

Detection of alpha activity in the electro-encephalogram (EEG) has been used extensively in neurophysiological studies. Previously applied alpha parameterisation techniques, which utilise the amplitude information from a pair of differential electrodes, are often susceptible to interference from artifact signals. This is an issue if the purpose of detecting the change in alpha wave synchronisation is the basis of an environmental control system (ECS). An alternative approach to alpha activity detection is proposed that utilises the information from an array of electrodes on the scalp to estimate the apparent location of alpha activity in the brain. Four methods are described that successfully detect the onset of alpha EEG increase following eye closure by monitoring the apparent location of alpha activity in the head. The methods use Bartlett beamforming, a four-sphere anatomical head model, the MUSIC algorithm and a new 'power vector' technique. Of the methods described, the power vector technique is found to be the most successful. The power vector technique detects the alpha increase associated with eye closure in times that are, on average, 33% lower than previously applied alpha detection methods.

摘要

脑电图(EEG)中阿尔法活动的检测已在神经生理学研究中广泛应用。以前应用的阿尔法参数化技术利用一对差分电极的幅度信息,往往容易受到伪迹信号的干扰。如果检测阿尔法波同步变化的目的是作为环境控制系统(ECS)的基础,这就是一个问题。本文提出了一种检测阿尔法活动的替代方法,该方法利用头皮上电极阵列的信息来估计大脑中阿尔法活动的表观位置。文中描述了四种方法,通过监测头部阿尔法活动的表观位置,成功检测出闭眼后阿尔法脑电图增加的起始。这些方法使用巴特利特波束形成、四球体解剖头部模型、MUSIC算法和一种新的“功率矢量”技术。在所描述的方法中,功率矢量技术被发现是最成功的。功率矢量技术检测与闭眼相关的阿尔法增加的时间,平均比以前应用的阿尔法检测方法低33%。

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