Brain-Computer Interface for Persons with Motor Disabilities - A Review
T. Anitha1, *, N. Shanthi1, R. Sathiyasheelan2, G. Emayavaramban3, T. Rajendran4
Identifiers and Pagination:Year: 2019
Issue: Suppl-1, M5
First Page: 127
Last Page: 133
Publisher Id: TOBEJ-13-127
Article History:Received Date: 19/02/2019
Revision Received Date: 14/10/2019
Acceptance Date: 18/10/2019
Electronic publication date: 17/12/2019
Collection year: 2019
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
A Brain-Computer Interface (BCI) is a communication medium, which restructures brain signals into respective commands for an external device.
A BCI allows its target users like persons with motor disabilities to act on their environment using brain signals without using peripheral nerves or muscles. In this review article, we have presented a view on different BCIs for humans with motor disabilities.
Results & Conclusion:
From the study, it is clear that the P300 based Electroencephalography (EEG)BCIs with Steady-State Visually Evoked Potential (SSVEP) non-parametric feature extraction techniques work with high efficiency in the major parameters like Information Bit Transfer Rate (ITR), Mutual Information (MI) rate and Low Signal to Noise Ratio (SNR) and achieve a maximum classification accuracy using Self Organized Fuzzy Neural Network (SOFNN).