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dc.contributor.authorAsyali, Musa H.
dc.contributor.authorGungor, Evrim
dc.contributor.authorArslan, Dilek Betul
dc.contributor.authorKorkmaz, Sumeyye
dc.contributor.authorYilmaz, Bulent
dc.date.accessioned2023-08-04T06:46:19Z
dc.date.available2023-08-04T06:46:19Z
dc.date.issued2014en_US
dc.identifier.issn0169-2607
dc.identifier.issn1872-7565
dc.identifier.otherWOS:000330137600026
dc.identifier.urihttps://doi.org/10.1016/j.cmpb.2013.11.010
dc.identifier.urihttps://hdl.handle.net/20.500.12573/1683
dc.description.abstractIn this study, we have analyzed electroencephalography (EEG) signals to investigate the following issues, (i) which frequencies and EEG channels could be relatively better indicators of preference (like or dislike decisions) of consumer products, (ii) timing characteristic of "like" decisions during such mental processes. For this purpose, we have obtained multi-channel EEG recordings from 15 subjects, during total of 16 epochs of 10 s long, while they were presented with some shoe photographs. When they liked a specific shoe, they pressed on a button and marked the time of this activity and the particular epoch was labeled as a LIKE case. No button press meant that the subject did not like the particular shoe that was displayed and corresponding epoch designated as a DISLIKE case. After preprocessing, power spectral density (PSD) of EEG data was estimated at different frequencies (4, 5, ... , 40 Hz) using the Burg method, for each epoch corresponding to one shoe presentation. Each subject's data consisted of normalized PSD values (NPVs) from all LIKE and DISLIKE cases/epochs coming from all 19 EEG channels. In order to determine the most discriminative frequencies and channels, we have utilized logistic regression, where LIKE/DISLIKE status was used as a categorical (binary) response variable and corresponding NPVs were the continuously valued input variables or predictors. We observed that when all the NPVs (total of 37) are used as predictors, the regression problem was becoming ill-posed due to large number of predictors (compared to the number of samples) and high correlation among predictors. To circumvent this issue, we have divided the frequency band into low frequency (LF) 4-19 Hz and high frequency (HF) 20-40 Hz bands and analyzed the influence of the NPV in these bands separately. Then, using the p-values that indicate how significantly estimated predictor weights are different than zero, we have determined the NPVs and channels that are more influential in determining the outcome, i. e., like/dislike decision. In the LF band, 4 and 5 Hz were found to be the most discriminative frequencies (MDFs). In the HF band, none of the frequencies seemed offer significant information. When both male and female data was used, in the LF band, a frontal channel on the left (F7-A1) and a temporal channel on the right (T6-A2) were found to be the most discriminative channels (MDCs). In the HF band, MDCs were central (Cz-A1) and occipital on the left (O1-A1) channels. The results of like timings suggest that male and female behavior for this set of stimulant images were similar. (C) 2013 Elsevier Ireland Ltd. All rights reserved.en_US
dc.language.isoengen_US
dc.publisherELSEVIER IRELAND LTDen_US
dc.relation.isversionof10.1016/j.cmpb.2013.11.010en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectNeuromarketingen_US
dc.subjectEEGen_US
dc.subjectPartialityen_US
dc.subjectPower spectral densityen_US
dc.subjectBurg methoden_US
dc.subjectLogisticen_US
dc.subjectRegressionen_US
dc.titleLike/dislike analysis using EEG: Determination of most discriminative channels and frequenciesen_US
dc.typearticleen_US
dc.contributor.departmentAGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümüen_US
dc.contributor.authorID0000-0003-2954-1217en_US
dc.contributor.institutionauthorYilmaz, Bulent
dc.identifier.volume113en_US
dc.identifier.issue2en_US
dc.identifier.startpage705en_US
dc.identifier.endpage713en_US
dc.relation.journalCOMPUTER METHODS AND PROGRAMS IN BIOMEDICINEen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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