A systematic review of the prediction of consumer preference using EEG measures and machine-learning in neuromarketing research

A systematic review of the prediction of consumer preference using EEG measures and machine-learning in neuromarketing research

Abstract Introduction The present paper discusses the findings of a systematic review of EEG measures in neuromarketing, identifying which EEG measures are the most robust predictor of customer preference in neuromarketing. The review investigated which TF effect (e.g., theta-band power), and ERP co...

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Bibliographic Details
Main Authors: Adam Byrne, Emma Bonfiglio, Colin Rigby, Nicky Edelstyn
Format: Article
Language:English
Published: SpringerOpen 2022-11-01
Series:Brain Informatics
Subjects:
EEG
ERP
Neuromarketing
Machine learning
Systematic review
Time–frequency
Online Access:https://doi.org/10.1186/s40708-022-00175-3

Internet

https://doi.org/10.1186/s40708-022-00175-3

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