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Enhancing the Reliability of EEG Cognitive State Analysis Using Blockchain and Semantic Inference

  • Journal of Internet of Things and Convergence
  • Abbr : JKIOTS
  • 2026, 12(3), 21
  • Publisher : The Korea Internet of Things Society
  • Research Area : Engineering > Computer Science > Internet Information Processing
  • Received : April 28, 2026
  • Accepted : June 22, 2026
  • Published : June 30, 2026

Guijung Kim 1

1백석대학교

Accredited

ABSTRACT

This study proposes an integrated framework to enhance the interpretability and reliability of EEG-based cognitive state analysis. The proposed method applies a Self-Organizing Map (SOM) for unsupervised clustering and employs ontology-based semantic inference to transform clustering results into interpretable cognitive states. In addition, a confidence model combining cluster stability, rule consistency, and feature stability is introduced to evaluate the quality of the results. A blockchain-based verification mechanism is incorporated to ensure data integrity and reproducibility. Experiments using the BCI Competition IV Dataset 2a show that the proposed method outperforms conventional approaches in clustering performance. The results also demonstrate improved interpretability and stable confidence estimation. Furthermore, the blockchain-based validation effectively detects data tampering and guarantees consistent reproducibility. Overall, the proposed framework improves not only accuracy but also interpretability and trustworthiness, suggesting its applicability in u-Health and real-time decision support systems.

Citation status

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