A review of disability EEG based wheelchair control system: Coherent taxonomy, open challenges and recommendations. (October 2018)

• Record Type: Journal Article
• Authors: Al-qaysi, Z.T.; Zaidan, B.B.; Zaidan, A.A.; Suzani, M.S.
• Is Part Of: Computer methods and programs in biomedicine. Volume 164(2018)
• Page Start: 221
• Page End: 237
• Publication Date: 2018-10
• Subjects: EEG -- Wheelchair -- Control system -- Brain–computer interface; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2018.06.012
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: Mapping the research landscape disability EEG based wheelchair control system into a coherent taxonomy. Figure out the motivation of using the disability EEG based wheelchair control system. Highlight the open challenges that hinder the utility disability EEG based wheelchair control system Recommendations lists to improve the acceptance of used the disability EEG based wheelchair control system Abstract: Context: Intelligent wheelchair technology has recently been utilised to address several mobility problems. Techniques based on brain–computer interface (BCI) are currently used to develop electric wheelchairs. Using human brain control in wheelchairs for people with disability has elicited widespread attention due to its flexibility. Objective: This study aims to determine the background of recent studies on wheelchair control based on BCI for disability and map the literature survey into a coherent taxonomy. The study intends to identify the most important aspects in this emerging field as an impetus for using BCI for disability in electric-powered wheelchair (EPW) control, which remains a challenge. The study also attempts to provide recommendations for solving other existing limitations and challenges. Methods: We systematically searched all articles about EPW control based on BCI for disability in three popular databases: ScienceDirect, IEEE and Web of Science. These databases contain numerous articles that considerably influenced this field and cover most of the relevant theoretical and technical issues. Results: We selected 100 articles on the basis of our inclusion and exclusion criteria. A large set of articles (55) discussed on developing real-time wheelchair control systems based on BCI for disability signals. Another set of articles (25) focused on analysing BCI for disability signals for wheelchair control. The third set of articles (14) considered the simulation of wheelchair control based on BCI for disability signals. Four articles designed a framework for wheelchair control based on BCI for disability signals. Finally, one article reviewed concerns regarding wheelchair control based on BCI for disability signals. Discussion: Since 2007, researchers have pursued the possibility of using BCI for disability in EPW control through different approaches. Regardless of type, articles have focused on addressing limitations that impede the full efficiency of BCI for disability and recommended solutions for these limitations. Conclusions: Studies on wheelchair control based on BCI for disability considerably influence society due to the large number of people with disability. Therefore, we aim to provide researchers and developers with a clear understanding of this platform and highlight the challenges and gaps in the current and future studies.