Probabilistic simulation framework for EEG-based BCI design

Umut Orhan, Hooman Nezamfar, Murat Akcakaya, Deniz Erdogmus, Matt Higger, Mohammad Moghadamfalahi, Andrew Fowler, Brian Roark, Barry Oken, Melanie Fried-Oken

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


A simulation framework could decrease the burden of attending long and tiring experimental sessions on the potential users of brain-computer interface (BCI) systems. Specifically during the initial design of a BCI, a simulation framework that could replicate the operational performance of the system would be a useful tool for designers to make design choices. In this manuscript, we develop a Monte Carlo-based probabilistic simulation framework for electroencephalography (EEG) based BCI design. We employ one event-related potential (ERP) based typing and one steady-state evoked potential (SSVEP) based control interface as testbeds. We compare the results of simulations with real-time experiments. Even though over- and underestimation of the performance is possible, the statistical results over the Monte Carlo simulations show that the developed framework generally provides a good approximation of the real-time system performance.

Original languageEnglish (US)
Pages (from-to)171-185
Number of pages15
JournalBrain-Computer Interfaces
Issue number4
StatePublished - Oct 1 2016


  • Electroencephalography
  • event-related potentials
  • simulation
  • steady-state visually evoked potentials

ASJC Scopus subject areas

  • Biomedical Engineering
  • Human-Computer Interaction
  • Behavioral Neuroscience
  • Electrical and Electronic Engineering


Dive into the research topics of 'Probabilistic simulation framework for EEG-based BCI design'. Together they form a unique fingerprint.

Cite this