Identifying the Effect of Cognitive Motivation with the Method Based on Temporal Association Rule Mining Concept

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Publication Details

Author listPhukhachee T., Maneewongvatana S., Chaiyanan C., Iramina K., Kaewkamnerdpong B.

PublisherMDPI

Publication year2024

Volume number24

Issue number9

Start page2857

ISSN14248220

eISSN1424-8220

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85192721994&doi=10.3390%2fs24092857&partnerID=40&md5=286a6a79c165aa7acaec7143c585fcfb

LanguagesEnglish-Great Britain (EN-GB)


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Abstract

Being motivated has positive influences on task performance. However, motivation could result from various motives that affect different parts of the brain. Analyzing the motivation effect from all affected areas requires a high number of EEG electrodes, resulting in high cost, inflexibility, and burden to users. In various real-world applications, only the motivation effect is required for performance evaluation regardless of the motive. Analyzing the relationships between the motivation-affected brain areas associated with the task’s performance could limit the required electrodes. This study introduced a method to identify the cognitive motivation effect with a reduced number of EEG electrodes. The temporal association rule mining (TARM) concept was used to analyze the relationships between attention and memorization brain areas under the effect of motivation from the cognitive motivation task. For accuracy improvement, the artificial bee colony (ABC) algorithm was applied with the central limit theorem (CLT) concept to optimize the TARM parameters. From the results, our method can identify the motivation effect with only FCz and P3 electrodes, with 74.5% classification accuracy on average with individual tests. © 2024 by the authors.


Keywords

ElectroencephalographyMotivationtemporal association rule miningVisual cognitive motivation task


Last updated on 2024-08-08 at 00:00