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REVIEW ARTICLE

Brain-Computer Interface for Persons with Motor Disabilities - A Review

T. Anitha1 , * Open Modal iD N. Shanthi1 iD R. Sathiyasheelan2 iD G. Emayavaramban3 iD T. Rajendran4 iD Authors Info & Affiliations
The Open Biomedical Engineering Journal • 17 December 2019 • REVIEW ARTICLE • DOI: 10.2174/1874120701913010127

Abstract

Aim /Objective:

A Brain-Computer Interface (BCI) is a communication medium, which restructures brain signals into respective commands for an external device.

Methodology:

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).

Keywords: Brain-Computer Interface (BCI), Non parametric Statistical Features, P300, Electroencephalography (EEG), Steady-State Visually Evoked Potential (SSVEP), non-parametric statistical feature extraction, Information Bit Transfer Rate (ITR), Mutual Information (MI), Signal to Noise Ratio (SNR) and Self Organized Fuzzy Neural Network (SOFNN).
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