Motor-Imagery EEG-Based BCIs in Wheelchair Movement and Control: A Systematic Literature Review.
Sensors (Basel)
; 21(18)2021 Sep 19.
Article
in English
| MEDLINE | ID: covidwho-1430953
ABSTRACT
The pandemic emergency of the coronavirus disease 2019 (COVID-19) shed light on the need for innovative aids, devices, and assistive technologies to enable people with severe disabilities to live their daily lives. EEG-based Brain-Computer Interfaces (BCIs) can lead individuals with significant health challenges to improve their independence, facilitate participation in activities, thus enhancing overall well-being and preventing impairments. This systematic review provides state-of-the-art applications of EEG-based BCIs, particularly those using motor-imagery (MI) data, to wheelchair control and movement. It presents a thorough examination of the different studies conducted since 2010, focusing on the algorithm analysis, features extraction, features selection, and classification techniques used as well as on wheelchair components and performance evaluation. The results provided in this paper could highlight the limitations of current biomedical instrumentations applied to people with severe disabilities and bring focus to innovative research topics.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Wheelchairs
/
Brain-Computer Interfaces
/
COVID-19
Type of study:
Experimental Studies
/
Reviews
/
Systematic review/Meta Analysis
Limits:
Humans
Language:
English
Year:
2021
Document Type:
Article
Affiliation country:
S21186285
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