Brain–computer interface for electric wheelchair based on alpha waves of EEG signal

Abstract Objectives Helping patients suffering from serious neurological diseases that lead to hindering the independent movement is of high social importance and an interdisciplinary challenge for engineers. Brain–computer interface (BCI) interfaces based on the electroencephalography (EEG) signal are not easy to use as they require time consuming multiple electrodes montage. We aimed to contribute in bringing BCI systems outside the laboratories so that it could be more accessible to patients, by designing a wheelchair fully controlled by an algorithm using alpha waves and only a few electrodes. Methods The set of eight binary words are designed, that allow to move forward, backward, turn right and left, rotate 45° as well as to increase and decrease the speed of the wheelchair. Our project includes: development of a mobile application which is used as a graphical user interface, real-time signal processing of the EEG signal, development of electric wheelchair engines control system and mechanical construction. Results The average sensitivity, without training, was 79.58% and specificity 97.08%, on persons who had no previous contact with BCI. Conclusions The proposed system can be helpful for people suffering from incurable diseases that make them closed in their bodies and for whom communication with the surrounding world is almost impossible.