Open AccessTopological Basis of Flat Electroencephalography’s State Space
Author(s) -
Tan Lit Ken,
Tahir Ahmad,
Lee Kee Quen,
Gan Yee Siang,
Wah Yen Tey,
Wong Kit
Publication year - 2017
Publication title -
asian journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2321-2462
DOI - 10.24203/ajet.v5i2.4756
Subject(s) - electroencephalography , perspective (graphical) , computer science , basis (linear algebra) , epileptic seizure , transformation (genetics) , pattern recognition (psychology) , plane (geometry) , artificial intelligence , topology (electrical circuits) , neuroscience , mathematics , psychology , biology , geometry , biochemistry , combinatorics , gene
Neuroinverse problem are often associated with complex neuronal activity. It involves locating problematic neuron which usually a highly challenging task. While epileptic foci localization is possible with the aid of EEG signals, it relies greatly on the ability to extract hidden information or pattern within EEG signals. Flat EEG being an enhancement of EEG is a way of viewing electroencephalograph on the real plane. In the perspective of dynamical systems, the equivalency of epileptic seizure and Flat EEG is important since the underlying structure of Flat EEG is dynamic. In this paper, a basis for the topological space of Flat EEG is presented. It is expected to facilitate in the constructions of dynamic transformation from epileptic seizure to Flat EEG. It provides a better understanding on Flat EEG itself.Â