A Brain Computer Interface for Robust Wheelchair Control Application Based on Pseudorandom Code Modulated Visual Evoked Potential.

Ali Mohebbi, Signe K.D. Engelsholm, Sadasivan Puthusserypady, Troels W. Kjaer, Carsten E. Thomsen, Helge Bjarup Dissing Sørensen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

In this pilot study, a novel and minimalistic Brain Computer Interface (BCI) based wheelchair control application was developed. The system was based on pseudorandom code modulated Visual Evoked Potentials (c-VEPs). The visual stimuli in the scheme were generated based on the Gold code, and the VEPs were recognized and classified using subject-specific algorithms. The system provided the ability of controlling a wheelchair model (LEGO R MINDSTORM R EV3 robot) in 4 different directions based on the elicited c-VEPs. Ten healthy subjects were evaluated in testing the system where an average accuracy of 97% was achieved. The promising results illustrate the potential of this approach when considering a real wheelchair application.
Original languageEnglish
Title of host publicationProceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PublisherIEEE
Publication date2015
Pages602-605
ISBN (Print)978-1-4244-9270-1
DOIs
Publication statusPublished - 2015
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Milano, Italy
Duration: 25 Aug 201529 Aug 2015
Conference number: 37

Conference

Conference37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Number37
Country/TerritoryItaly
CityMilano
Period25/08/201529/08/2015

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