Development of a brain computer interface based on steady-state visual evoked potential with multiple intermittent photo stimulation

Abstract

BackgroundBrain–computer interfaces (BCIs) are systems able to convert the brain activity into electrical signals, which may be used to take decisions and/or control an artificial device. They may be classified as either passive or active. In this latter kind of BCI, changes in the electroencephalogram (EEG) in response to an external stimulus are used to decode a command or an order to an external device. New methodThis project aims at developing a stable and active BCI based on steady-state visual evoked potential (SSVEP) by intermittent photic stimulation using different LEDs with high stimulation frequencies to improve visual comfort. Spatial filters, calculated automatically during a training phase, are used in pre-processing to enhance the EEG signals and their desired features. Hence, we present an approach to automatically calculate the optimum spatial filters to detect the SSVEP at each stimulation frequency used. ResultsExperiments with 10 subjects allowed determining which detection method, based on either the instantaneous power or the magnitude-squared coherence, is more suitable for decoding the commands the BCI has to give out. Comparison with existing methodsDifferently to other methods, this one chooses automatically the best spatial filter during the training phase and uses multiple stimulation frequencies with high frequencies to avoid annoyance and preventing risks related to photo-epilepsy. ConclusionsA stable and active BCI was designed with a correct detection rate within 74–76%, ITR value between 19 and 26 [bit/min] and response delay for the detection between two consecutive stimulation frequencies within 2–2.5 s.