Determining the effect of emotional images brightness on EEG signals by classification algorithms
Yazarlar (4)
Dr. Öğr. Üyesi Kübra Eroğlu Nişantaşı Üniversitesi, Türkiye
Prof. Dr. Onur Osman Nişantaşı Üniversitesi, Türkiye
Prof. Dr. Temel Kayıkçıoğlu Karadeniz Teknik Üniversitesi, Türkiye
Prof. Dr. Pınar Kurt COMBİL İzmir Demokrasi Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
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| Dergi Adı | Multidimensional Systems and Signal Processing (Q2) | ||
| Dergi ISSN | 0923-6082 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | Türkçe | Basım Tarihi | 01-2022 |
| Cilt / Sayı / Sayfa | – / 3 / – | DOI | 10.1007/s11045-022-00821-3 |
| Makale Linki | http://dx.doi.org/10.1007/s11045-022-00821-3 | ||
| UAK Araştırma Alanları |
Bilişsel Psikoloji
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| Özet |
| This study demonstrated the effects of image brightness on brain activity in neuroscience research, in which the brightness of emotional images had not been taken into account. Electroencephalography recordings from 14 electrode sites of 31 healthy participants were examined during the presentation of original and bright versions of neutral, pleasant and unpleasant images. Power spectra of the recordings were obtained using the short time Fourier transform. The features were extracted from the power spectra for specific time–frequency windows and data obtained from features were classified using support vector machine (SVM), partial least squares regression (PLSR) and k-nearest neighbor (k-NN) algorithms between the original and bright groups for three emotional contents. New features were created with feature combinations providing high classification accuracy. The data obtained from new features … |
| Anahtar Kelimeler |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Google Scholar | 4 |