Iranian Journal of Biomedical Engineering (IJBME)
نشریه علمی مهندسی پزشکی زیستی

Nonlinear EEG Processing and Statistical Analysis in the Study of Preference and Liking a Product

Document Type : Full Research Paper

Authors

Somayeh Raiesdana 1
Samaneh Safari 2

1 Assistant Professor, Biomedical Engineering Group, Department of Electrical, Biomedical and Mechatronics Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

2 M.Sc. Biomedical Engineering Group, Department of Electrical, Biomedical and Mechatronics Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

https://doi.org/10.22041/ijbme.2019.103139.1442
Abstract
In this study, a neuromarketing project was conducted via EEG signal processing in which the individuals’ interest for buying a relatively luxurious decorative product (which has a relative advantage in exports based on commonly evaluated criteria and indicators in economic) was evaluated. EEG signals of 24 participants during observing and selecting gemstone images were recorded and processed in order to analyze statistical significance of brain activity variations involved in the emotional (liking) and the decision making (choosing) processes. The recorded signals during the stimulation and selection phases were pre-processed in several steps to remove the existing noises and artifacts. Then, the 19-channel EEGs were processed via multiple tools to indicate active brain regions while watching gemstones. Brain mapping and regional analysis indicated that the occipital>frontal>limbic regions were more activated than other regions. Moreover, the left hemisphere has been more active than the right hemisphere. At the next step, nonlinear entropy feature of each signal segment was extracted to be used for training a neurofuzzy system which is an automatic classifier that learns to classify the individuals’ choices. The classification has resulted in 86.25% precision and 87.4% accuracy in a three-class classification task (including two pleasant selections and one unpleasant selection). At the final step, using a questionnaire filled by participants following the recording session, a number of statistical analyses were performed over the self-conscious and unconscious by means of statistical tools including t-test, analysis of variance and regression. The results of statistical tests indicated that there are significant differences for the cognition of liking or preferring among different choices and based on the selections made by women and men. Furthermore, the lack of existence of a significant difference between conscious and unconscious choices were rejected. 

Keywords

EEG Signal
Neuromarketing
Independent Component Analysis
Approximate Entropy
Neurofuzzy
Statistical Analysis
Brain Mapping

Subjects

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Iranian Journal of Biomedical Engineering (IJBME)
Volume 13, Issue 2
Summer 2019
Pages 117-134

  • Receive Date 01 February 2019
  • Revise Date 25 May 2019
  • Accept Date 12 July 2019

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