Decoding SSVEP responses based on PARAFAC decomposition

Nikolay V. Manyakov*, Nikolay Chumerin, Adrien Combaz, Arne Robben, Marijn van Vliet, Marc M. Van Hulle

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)


In this position paper, we investigate whether a parallel factor analysis (Parafac) decomposition is beneficial to the decoding of steady-state visual evoked potentials (SSVEP) present in electroencephalogram (EEG) recordings taken from the subject's scalp. In particular, we develop an automatic algorithm aimed at detecting the stimulation frequency after Parafac decomposition. The results are validated on recordings made from 54 subjects using consumer-grade EEG hardware (Emotiv's EPOC headset) in a real-world environment. The detection of one frequency among 12, 4 and 2 possible was considered to assess the feasibility for Brain Computer Interfacing (BCI). We determined the frequencies subsets, among all subjects, that maximize the detection rate.

Original languageEnglish
Title of host publicationBIOSIGNALS 2012 - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing
Number of pages5
Publication statusPublished - 13 Jun 2012
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Bio-inspired Systems and Signal Processing - Vilamoura, Portugal
Duration: 1 Feb 20124 Feb 2012


ConferenceInternational Conference on Bio-inspired Systems and Signal Processing
Abbreviated titleBIOSIGNALS


  • Decoding
  • EEG
  • Parafac
  • Steady-state visual evoked potential


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