Probabilistic Simulation Framework for EEG-Based BCI Design

Overview

Journal Brain Comput Interfaces (Abingdon)

Date 2017 Dec 19

PMID 29250562

Citations 5

Authors

Umut Orhan

Hooman Nezamfar

Murat Akcakaya

Deniz Erdogmus

Matt Higger

Mohammad Moghadamfalahi

Andrew Fowler

Brian Roark

Barry Oken

Melanie Fried-Oken

Affiliations

Soon will be listed here.

Abstract

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 under estimation 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.

Citing Articles

Gonzalez-Navarro P, Celik B, Moghadamfalahi M, Akcakaya M, Fried-Oken M, Erdogmus D Front Hum Neurosci. 2022; 15:788258.

PMID: 35145386 PMC: 8821166. DOI: 10.3389/fnhum.2021.788258.

On Analysis of Active Querying for Recursive State Estimation.

Kocanaogullari A, Akcakay M, Erdogmus D IEEE Signal Process Lett. 2019; 25(6):743-747.

PMID: 31871396 PMC: 6927333. DOI: 10.1109/LSP.2018.2823271.

An Active RBSE Framework to Generate Optimal Stimulus Sequences in a BCI for Spelling.

Moghadamfalahi M, Akcakaya M, Nezamfar H, Sourati J, Erdogmus D IEEE Trans Signal Process. 2019; 65(20):5381-5392.

PMID: 31871392 PMC: 6927477. DOI: 10.1109/TSP.2017.2728500.

Optimal Query Selection Using Multi-Armed Bandits.

Kocanaogullari A, Marghi Y, Akcakaya M, Erdogmus D IEEE Signal Process Lett. 2019; 25(12):1870-1874.

PMID: 31588169 PMC: 6777547. DOI: 10.1109/LSP.2018.2878066.

An Event-Driven AR-Process Model for EEG-Based BCIs With Rapid Trial Sequences.

Gonzalez-Navarro P, Marghi Y, Azari B, Akcakaya M, Erdogmus D IEEE Trans Neural Syst Rehabil Eng. 2019; 27(5):798-804.

PMID: 30869624 PMC: 6629584. DOI: 10.1109/TNSRE.2019.2903840.

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