EEG Artefact Signal Filtering in Dynamic Motion Simulators
EEG Artefact Signal Filtering in Dynamic Motion Simulators
ABSTRACT: The performance of electroencephalograph (EEG)-based brain-computer interface (BCI) systems is susceptible to external influences, typically due to movement of the subject. Static flight simulators are the norm for this type of measurement in reduced risk flight training; however modern day simulators require a new level of realism. Next-generation flight simulators, such as the Deakin University Haptically Enabled Universal Motion Simulator, expose the pilot to external ‘G’ forces by physical moving the entire cockpit and pilot, motions which increase the likelihood of unwanted EEG artefacts. The filtering techniques are based on a custom designed approach to overcome the dynamic nature of the flight simulator; the techniques are based on Extended Kalman Filters to accommodate for the non-linearity of the EEG acquired signals. In this paper, the effectiveness of the proposed BCI system is presented in the dynamic nature of the simulator. The proposed BCI paradigm is tested and evaluated under real test conditions and the results analysed and compared to that of a static flight simulator.
IITSEC 2014