Stimulation Effects in SSVEP-Based BCIs

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dc.contributor.advisorDesain, P.W.M.
dc.contributor.advisorGarcia Molina, G.
dc.contributor.authorBieger, J.E.
dc.date.issued2010-08-17
dc.description.abstractBrain-Computer Interfaces (BCIs) enable people to control appliances without involving the normal output pathways of peripheral nerves and muscles. A particularly promising type of BCI is based on the Steady-State Visual Evoked Potential (SSVEP). Users can select commands by focusing their attention on repetitive visual stimuli (RVSi) that change one of their properties (e.g. color or pattern) with a certain frequency. These properties as well as the device the RVSi are rendered on, can greatly affect the performance, applicability, comfort and safety of the BCI. Despite this fact, stimulation properties have received fairly little attention in the BCI literature to this date. Furthermore, a heavy emphasis is placed on BCI performance to the detriment of other important factors such as comfort and safety. The research reported in this document aims at studying the effects of stimulation properties on performance as well as comfort of SSVEP-based BCIs. Research was performed in both offline and online settings, using a custom made high-performance BCI. Comfort was measured using a custom questionnaire. A large variability across subjects was found, but the results confirm that stimulation properties have a considerable impact on performance and comfort of SSVEPbased BCIs. In general, a large difference between stimulation states is beneficial for BCI performance, but detrimental to user comfort. A couple of configurations were found that provide a good compromise between comfort and performance. Keywords: Brain-Computer Interfacing, BCI, Steady-State Visual Evoked Potential, SSVEP, Repetitive Visual Stimulation, Photic Drivingen_US
dc.identifier.urihttp://theses.ubn.ru.nl/handle/123456789/173
dc.language.isoenen_US
dc.thesis.facultyFaculteit der Sociale Wetenschappenen_US
dc.thesis.specialisationMaster Artificial Intelligenceen_US
dc.thesis.studyprogrammeArtificial Intelligenceen_US
dc.thesis.typeMasteren_US
dc.titleStimulation Effects in SSVEP-Based BCIsen_US
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