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Normal Spatial Channel for Working on the Order of EEG utilizing Fake Brain Organization

Shreyas .

Abstract


The classifier performance of electroencephalogram (EEG) data in motor imagery machine learning varies by subject. When used on a variety of subjects, the classifier's performance suffers. The common spatial pattern (CSP) method is suggested as a solution to this problem. The dataset contains 9 subjects EEG information. Using an artificial neural network (ANN), a common spatial pattern is used in feature extraction to improve the classifier for various subjects. Random forest is used to train the accuracy of the data on the basis of the classification. When compared to the existing method, the obtained results show a performance improvement of 0.96 percent.


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