Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (1)

Search Parameters:
Keywords = brain controller wheelchair (BCW)

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
29 pages, 2302 KiB  
Review
Motor-Imagery EEG-Based BCIs in Wheelchair Movement and Control: A Systematic Literature Review
by Arrigo Palumbo, Vera Gramigna, Barbara Calabrese and Nicola Ielpo
Sensors 2021, 21(18), 6285; https://doi.org/10.3390/s21186285 - 19 Sep 2021
Cited by 91 | Viewed by 10739
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Brain–Computer Interfaces: Advances and Challenges)
Show Figures

Figure 1

Back to TopTop