This paper presents a review of the state of the art regarding wheelchairs driven by a brain–computer interface. Using a brain-controlled wheelchair (BCW), disabled users could handle a wheelchair through their brain activity, granting autonomy to move through an experimental environment. A classification is established, based on the characteristics of the BCW, such as the type of electroencephalographic signal used, the navigation system employed by the wheelchair, the task for the participants, or the metrics used to evaluate the performance. Furthermore, these factors are compared according to the type of signal used, in order to clarify the differences among them. Finally, the trend of current research in this field is discussed, as well as the challenges that should be solved in the future.

Certain diseases affect brain areas that control the movements of the patients’ body, thereby limiting their autonomy and communication capacity. Research in the field of Brain-Computer Interfaces aims to provide patients with an alternative communication channel not based on muscular activity, but on the processing of brain signals. Through these systems, subjects can control external devices such as spellers to communicate, robotic prostheses to restore limb movements, or domotic systems. The present work focus on the non-muscular control of a robotic wheelchair. A proposal to control a wheelchair through a Brain–Computer Interface based on the discrimination of only two mental tasks is presented in this study. The wheelchair displacement is performed with discrete movements. The control signals used are sensorimotor rhythms modulated through a right-hand motor imagery task or mental idle state. The peculiarity of the control system is that it is based on a serial auditory interface that provides the user with four navigation commands. The use of two mental tasks to select commands may facilitate control and reduce error rates compared to other endogenous control systems for wheelchairs. Seventeen subjects initially participated in the study; nine of them completed the three sessions of the proposed protocol. After the first calibration session, seven subjects were discarded due to a low control of their electroencephalographic signals; nine out of ten subjects controlled a virtual wheelchair during the second session; these same nine subjects achieved a medium accuracy level above 0.83 on the real wheelchair control session. The results suggest that more extensive training with the proposed control system can be an effective and safe option that will allow the displacement of a wheelchair in a controlled environment for potential users suffering from some types of motor neuron diseases.

Brain-computer interface (BCI) spellers allow severe motor-disabled patients to communicate using their brain activity without muscular mobility. Different visual configurations of the widely studied P300-based BCI speller had been assessed with healthy and motor-disabled users. However, the speller size (in terms of cm) had only been assessed for healthy subjects. We think that the speller size might be limiting for some severely motor-disabled patients with restricted head and eye movements. The usability of three speller sizes was assessed for seven patients diagnosed with amyotrophic lateral sclerosis (ALS) and a participant diagnosed with Duchenne muscular dystrophy (DMD). This is the first usability evaluation of speller size with severely motor-disabled participants. Effectiveness (in the online results) and efficiency (in the workload test) of the medium speller was remarkably better. Satisfaction was significantly the highest with the medium size speller and the lowest with the small size. These results correlate with previously described findings in healthy subjects. In conclusion, the speller size should be considered when designing a speller paradigm, especially for motor-disabled individuals, since it might affect their performance and user experience while controlling a BCI speller.

In this paper, an asynchronous brain–computer interface is presented that enables the control of a wheelchair in virtual environments using only one motor imagery task. The control is achieved through a graphical intentional control interface with three navigation commands (move forward, turn right, and turn left) which are displayed surrounding a circle. A bar is rotating in the center of the circle, so it points successively to the three possible commands. The user can, by motor imagery, extend this bar length to select the command at which the bar is pointing. Once a command is selected, the virtual wheelchair moves in a continuous way, so the user controls the length of the advance or the amplitude of the turns. Users can voluntarily switch from this interface to a noncontrol interface (and vice versa) when they do not want to generate any command. After performing a cue-based feedback training, three subjects carried out an experiment in which they had to navigate through the same fixed path to reach an objective. The results obtained support the viability of the system.