Blockchain Enabled EEG Neuromarketing Framework for Secure and Intelligent Consumer Electronics

Document Type

Article

Source of Publication

IEEE Transactions on Consumer Electronics

Publication Date

1-1-2026

Abstract

The convergence of sensing, communication, computing, and control is transforming consumer electronics into intelligent, adaptive systems. This work proposes a blockchain-enabled neuromarketing framework that decodes neural correlates of perception, attention, and emotion from electroen-cephalography (EEG) and integrates the inferred outcomes into secure, real-time consumer platforms. EEG data were collected from 40 participants using a 19-channel system while viewing six advertisements. Following preprocessing, artifact removal, and wavelet-based feature extraction, 240 features spanning time, frequency, and time-frequency domains were obtained. Dimensionality reduction via principal component analysis and class balancing prepared the data for artificial neural network classification with k-fold validation. The framework achieved accuracies of 85.16% (perception at Fp2), 80.62% (attention at Fp1), and 73.91% (emotion at F8), highlighting the role of frontal and parietal circuits. A Hyperledger-based blockchain layer enabled secure communication and adaptive control, achieving 145 transactions per second, 420 ms average latency, and only 2.1% inference overhead, with storage growth below 5 MB. These results demonstrate that combining EEG-based cognitive inference with blockchain trust mechanisms enables intelligent, secure, and privacy-preserving consumer electronics.

ISSN

0098-3063

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Disciplines

Computer Sciences

Keywords

Artificial Neural Networks, Blockchain, Consumer Electronics, EEG, Neural Circuits, Neuromarketing, Secure Computing

Scopus ID

105032801054

Indexed in Scopus

yes

Open Access

no

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