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Abstract

Brain-Machine Communication (BMC) help to the disabled people those are not capable of using their hands or other body organs to communicate with the machine. The main objective of BMC systems is to convert brain signal into a digital signal that can understand by machine. The major problem in BMC research filed is to extract the features of brain signals, which are random time varying in nature and how to classify these features with desirable accurately. Extraction of features can be using various techniques, numbers of linear and non-linear feature extraction methods exist. Earlier brain signal analysis was only being done using visual inspection. Therefore, this manual inspection of brain signal is very limited to standardization or statistical analysis. However, several techniques have developed to quantify the brain signal’s information. The motive of this research is to provide a brief detail of brain signals and BMC system. The article is about the methods that are using to extract the feature of the brain signal.

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