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Abstract In the last few decades, bio-robotics applications such as exoskeletons, prosthetics and robotic wheelchairs have progressed from machines in science fiction to nearly commercialized products. Though there are still several challenges associated with electromyography (EMG) signals, the advances in use of EMG signals for controlling such bio-robotics applications have been enormous. Similarly, recent trends and attempts in developing electroencephalography- (EEG) based control methods have shown the potential of this area in the modern bio-robotics field. However, the EEG-based control methods are also yet to be perfected. A new approach of combining both these control methods, which take the advantages, and diminish the disadvantages, of each system might therefore be a promising approach. In this paper, we review hybrid fusion of EMG- and EEG-based control approaches in the bio-robotics field which have been attempted or developed to date. We provide a design overview of the method and consider the main features and merits/disadvantagages for the approaches that have been analyzed. We also discuss the current challenges regarding these hybrid EEG-EMG control approaches and propose some potential future directions.
Lalitharatne et al. (Tue,) studied this question.