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

Abstract

© 2019 Anitha et al. 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) nonparametric 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).