Detection of Familiar and Unfamiliar faces from EEG

face recognition from EEG


  • Navin Vanzara Government Engineering College, Gandhinagar
  • Chintan P. Shah Government Engineering College, Gandhinagar
  • Avani Vithalani Government Engineering College, Gandhinagar


Face perception, ICA decomposition, EEGLAB (MATLAB extension), SPA, independent T-test, Medical signal processing


Face recognition is a complex cognitive task that involves a distributed network of neural sources. While some components of this network have been identified, the temporal sequence of these components is not well understood yet. This study contains the detection of familiar or unfamiliar faces by using the event-related potential (ERP) response from the recorded EEG signal from subjects when they were introduced to stimulus as familiar faces, unfamiliar faces and scrambled faces, this study includes the dataset which contain the EEG data from 18 subjects for face recognition task, this recorded data is being used to detect if there is any significant difference recorded EEG data for type of faces. ERP artifacts based on the variance of components decomposed by PCA, the results achieved by using ICA and SPA then compared with each other to make the exact and accurate decision on the EEG response for a familiar face and unfamiliar faces.



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Author Biographies

  • Navin Vanzara, Government Engineering College, Gandhinagar

    Biomedical Engineering Department

  • Chintan P. Shah, Government Engineering College, Gandhinagar

    Biomedical Engineering Department

  • Avani Vithalani, Government Engineering College, Gandhinagar

    Electronics and Communication Engineering Department






Biomedical and Pharmaceutical Sciences


How to Cite

Vanzara, N., Shah, C. P., & Vithalani, A. (2023). Detection of Familiar and Unfamiliar faces from EEG. Journal of Integrated Science and Technology, 12(1), 715.

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