Motor-Imagery EEG-based BCIs in Wheelchairs Movement and Control: A
Systematic Literature Review
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, and 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 in the
pandemic context of Covid-19 and bring focus to innovative research
topics.