%X Electroencephalography (EEG) signals have great impact on the development of assistive rehabilitation devices. These signals are used as a popular tool to investigate the functions and the behavior of the human motion in recent research. The study of EEG-based control of assistive devices is still in early stages. Although the EEG-based control of assistive devices has attracted a considerable level of attention over the last few years, few studies have been carried out to systematically review these studies, as a means of offering researchers and experts a comprehensive summary of the present, state-of-the-art EEG-based control techniques used for assistive technology. Therefore, this research has three main goals. The first aim is to systematically gather, summarize, evaluate and synthesize information regarding the accuracy and the value of previous research published in the literature between 2011 and 2018. The second goal is to extensively report on the holistic, experimental outcomes of this domain in relation to current research. It is systematically performed to provide a wealthy image and grounded evidence of the current state of research covering EEG-based control for assistive rehabilitation devices to all the experts and scientists. The third goal is to recognize the gap of knowledge that demands further investigation and to recommend directions for future research in this area. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.
%K Biological organs; Brain computer interface; Electric grounding; Electroencephalography; Electrophysiology; Exoskeleton (Robotics), Assistive rehabilitations; Assistive technology; Brain machine interface; Control techniques; Lower limb; Recent researches; State of research; Upper limbs, Behavioral research
%D 2018
%N 10
%R 10.3390/s18103342
%O cited By 75
%L scholars9883
%J Sensors (Switzerland)
%T Eeg-based control for upper and lower limb exoskeletons and prostheses: A systematic review
%I MDPI AG
%A M.S. Al-Quraishi
%A I. Elamvazuthi
%A S.A. Daud
%A S. Parasuraman
%A A. Borboni
%V 18