Design of Low-Cost Steady State Visually Evoked Potential-Based Brain Computer Interface Using OpenBCI and Neuromore

Many patients suffer from neuromuscular diseases that prevent them from controlling their muscles. This motion limitation makes them fully reliable on others. This work presents a design of a low-cost brain-computer interface (BCI) system with which an electrical wheelchair is controlled directly by the patient's electroencephalogram (EEG). The design of the system is based on steady state visually evoked potentials (SSVEPs). Four groups of flickering stimuli are used in a graphical interface. To navigate the wheelchair, the user focusses his sight in the desired direction on the graphical interface to produce the corresponding SSVEP signal. The signal is acquired from the user's brain and processed using a proposed SSVEP detection algorithm. Based on the output of the algorithm, a command (forward, backward, left, or right) is translated to control the wheelchair. For the offline analysis, a comparison between O1 and O2 positions was done. Based on the obtained results, O2 gave the highest amplitude for 60% of the subjects. An additional experiment was done to choose the optimal stimulus colour. It was found that green/black is the best option that was both comfortable and provided a strong signal. For the real-time analysis, Neuromore software was used to develop the detection algorithm used for controlling the wheelchair prototype.