Prediction of Inefficient BCI Users based on Cognitive Skills and Personality Traits

Laura Hagedorn, Maryam Alimardani

Research output: Contribution to conference โ€บ Paper โ€บ Scientific โ€บ peer-review


BCI inefficiency is one of the major challenges of Motor Imagery Brain-Computer Interfaces (MI-BCI). Past research suggests that certain cognitive skills and personality traits correlate with MI-BCI real-time performance. Other studies have examined sensorimotor rhythm changes (known as ๐œ‡ suppression) as a valuable indicator of successful execution of the motor imagery task. This research aims to combine these insights by investigating whether cognitive factors and personality traits can predict a userโ€™s ability to modulate ๐œ‡ rhythms during a MI-BCI task. Data containing 55 subjects who completed a MI task was employed, and a stepwise linear regression model was implemented to select the most relevant features for ๐œ‡ suppression prediction. The most accurate model was based on: Spatial Ability, Visuospatial Memory, Autonomy, and Vividness of Visual Imagery. Further correlation analyses showed that a novice userโ€™s ๐œ‡ suppression during a MI-BCI task can be predicted based on their visuospatial memory, as measured by the Design Organization Test (DOT).
Original languageEnglish
Publication statusPublished - Dec 2021
EventInternational Conference on Neural Information Processing -
Duration: 8 Dec 2021 โ†’ 12 Dec 2021


ConferenceInternational Conference on Neural Information Processing
Period8/12/21 โ†’ 12/12/21


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