Affiliations: [a] Department of Mechanical Engineering, The University of Alabama, Tuscaloosa, USA
| [b] Department of Educational Studies in Psychology, Research Methodology, and Counseling, The University of Alabama, Tuscaloosa, USA
Correspondence:
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Corresponding author. Daniel J. Fonseca, Ph.D., Associate Professor, Mechanical Engineering, The University of Alabama, P.O. Box 860276, Tuscaloosa, 35487, Alabama, USA. Tel.: +1 205 348 3337; E-mail: [email protected].
Abstract: This paper deals with the design and development of a novel approach, centered on the creation and development of a fuzzy controller to analyze electroencephalogram (EEG) data. The fuzzy controller makes use of the functions associated with the different regions of the brain to correlate multiple Brodmann areas to several outputs, where a normal analysis would associate only one region to one output. This controller was designed to quickly adapt to any data imported into it. The current implemented framework supports a math study. The math subjects’ outputs were attuned to their related study which involved transcranial direct current stimulation (tDCS), which is a form of neurostimulation. Anode affinity, cathode affinity, calculation, memory, and decision making were the outputs focused on for the math study. This task is best suited to a fuzzy controller since interactions between Brodmann areas can be analyzed and the contributions of each area accounted for by indicating which regions have stronger and weaker effects on any given output.
Keywords: Neurological activation, transcranial direct current stimulation, EEG, fuzzy controller, math enhancement
