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http://dx.doi.org/10.9718/JBER.2007.28.2.258

Feasibility Study of EEG-based Real-time Brain Activation Monitoring System  

Chae, Hui-Je (Department of Biomedical Engineering, Yonsei University)
Im, Chang-Hwan (Department of Biomedical Engineering, Yonsei University)
Lee, Seung-Hwan (Department of Neuropsychiatry, Inje University Ilsan-Paik Hospital)
Publication Information
Journal of Biomedical Engineering Research / v.28, no.2, 2007 , pp. 258-264 More about this Journal
Abstract
Spatiotemporal changes of brain rhythmic activity at a certain frequency have been usually monitored in real time using scalp potential maps of multi-channel electroencephalography(EEG) or magnetic field maps of magnetoencephalography(MEG). In the present study, we investigate if it is possible to implement a real-time brain activity monitoring system which can monitor spatiotemporal changes of cortical rhythmic activity on a subject's cortical surface, neither on a sensor plane nor on a standard brain model, with a high temporal resolution. In the suggested system, a frequency domain inverse operator is preliminarily constructed, considering the individual subject's anatomical information, noise level, and sensor configurations. Spectral current power at each cortical vertex is then calculated for the Fourier transforms of successive sections of continuous data, when a single frequency or particular frequency band is given. An offline study which perfectly simulated the suggested system demonstrates that cortical rhythmic source changes can be monitored at the cortical level with a maximal delay time of about 200 ms, when 18 channel EEG data are analyzed under Pentium4 3.4GHz environment. Two sets of artifact-free, eye closed, resting EEG data acquired from a dementia patient and a normal male subject were used to show the feasibility of the suggested system. Factors influencing the computational delay are investigated and possible applications of the system are discussed as well.
Keywords
EEG; MEG; brain mapping; inverse problem; real-time brain activation monitoring system; cortical rhythmic activity; frequency domain minimum norm estimation;
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