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).
Highlights
The human brain has a huge network of nervous cells/neurons
Brain-Computer Interface (BCI) study [27] presents a high-speed speller BCI with a rate of conveying 40 characters that have been presented for 13 subjects involving in visual stimulus, this study proves that State Visually Evoked Potential (SSVEP) has been a promising analysis
In SSVEP based visual stimulus,Self Organized Fuzzy Neural Network (SOFNN) Classifiers are more predominant in processing the raw EEG signals such that it spontaneously evokes Mu and Beta frequencies for Right and left-hand motor imagery movements and achieves classification accuracy with high Information Bit Transfer Rate (ITR) and low Signal to Noise Ratio (SNR) [49 - 60]
Summary
The neurons fire inside the brain and produce an electrical signal. These neurons transmit information from the brain to discretionary muscles to control the motor organs [1]. When the neurons are not able to transmit signals among the brain and nervous system, these disorders lead to coma and paralysis. Such kind of individuals needs Brain-Computer Interface (BCI) for communication [2]. BCI systems enable a person with motor disabilities to send commands to a device by means of brain signals [3,4]. In order to control a BCI, the user must have to produce brain activity patterns that can be transmitted to the system and translated into commands [5]
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