A survey on robots controlled by motor imagery brain-computer interfaces
Jincai Zhang, Mei Wang
Abstract
A brain-computer interface (BCI) can provide a communication approach conveying brain information to the outside. Especially, the BCIs based on motor imagery play the important role for the brain-controlled robots, such as the rehabilitation robots, the wheelchair robots, the nursing bed robots, the unmanned aerial vehicles and so on. In this paper, the developments of the robots based on motor imagery BCIs are reviewed from three aspects: the electroencephalogram (EEG) evocation paradigms, the signal processing algorithms and the applications. First, the different types of the brain-controlled robots are reviewed and classified from the perspective of the evocation paradigms. Second, the relevant algorithms for the EEG signal processing are introduced, which including feature extraction methods and the classification algorithms. Third, the applications of the motor imagery brain-controlled robots are summarized. Finally, the current challenges and the future research directions of the robots controlled by the motor imagery BCIs are discussed.