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

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.