Consumer Preference Estimation Using EEG Signals and Deep Learning EEG Sinyalleri ve Derin Öğrenme Kullanılarak Tüketici Beğeni Durum Kestirimi

CEYLAN B., Çekiç Y., Akan A.

32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024, Mersin, Türkiye, 15 - 18 Mayıs 2024 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu61531.2024.10601136
  • Basıldığı Şehir: Mersin
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: advertisement, Deep Learning, EEG, emotional state, liking status, neuromarketing, STFT
  • İstanbul Yeni Yüzyıl Üniversitesi Adresli: Evet

Özet

Emotion estimation is an extremely critical and current research topic for human-computer interaction. In this study, a liking estimation method using electroencephalogram (EEG) signals is proposed to be used in neuromarketing studies. EEG data recorded while participants watch the advertisement videos of two different automobile brands are processed with deep learning techniques to estimate their liking status. After watching the videos, participants were presented with selected image sections from the advertisements (front view, console, side view, rear view, stop lamp, brand logo and front grille) and were asked to rate their liking by scoring from 1 to 5. EEG signals corresponding to these regions were converted into a two dimensional and RGB colored image using the short-time Fourier transform (STFT) method, and liking status was estimated using Deep Learning. The successful results obtained show that the proposed method can be used in neuromarketing studies.