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The use of shared control techniques has a profound impact on the performance of a robotic assistant controlled by human brain signals. However, this shared control usually provides assistance to the user in a constant and identical manner each time. Creating an adaptive level of assistance, thereby complementing the user's capabilities at any moment, would be more appropriate. The better the user can do by himself, the less assistance he receives from the shared control system; and vice versa. In order to do this, we need to be able to detect when and in what way the user needs assistance. An appropriate assisting behaviour would then be activated for the time the user requires help, thereby adapting the level of assistance to the specific situation. This paper presents such a system, helping a brain-computer interface (BCI) subject perform goal-directed navigation of a simulated wheelchair in an adaptive manner. Whenever the subject has more difficulties in driving the wheelchair, more assistance will be given. Experimental results of two subjects show that this adaptive shared control increases the task performance. Also, it shows that a subject with a lower BCI performance has more need for extra assistance in difficult situations, such as manoeuvring in a narrow corridor.