Affiliations 

  • 1 Smart Assistive and Rehabilitative Technology (SMART) Research Group & Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar 32610, Malaysia. eng.mgd@gmail.com
  • 2 Smart Assistive and Rehabilitative Technology (SMART) Research Group & Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar 32610, Malaysia. irraivan_elamvazuthi@utp.edu.my
  • 3 Smart Assistive and Rehabilitative Technology (SMART) Research Group & Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar 32610, Malaysia. sitiasmah.daud@utp.edu.my
  • 4 School of Engineering, Monash University Malaysia, Bandar Sunway 46150, Malaysia. s.parasuraman@monash.edu
  • 5 Mechanical and Industrial Engineering Department, Universita degli Studi di Brescia, Via Branze, 38-25123 Brescia, Italy. alberto.borboni@unibs.it
Sensors (Basel), 2018 Oct 07;18(10).
PMID: 30301238 DOI: 10.3390/s18103342

Abstract

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.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.