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http://dx.doi.org/10.7471/ikeee.2019.23.2.727

Electroencephalogram(EEG) Activation Changes and Correlations of signal with EMG Output by left and right biceps  

Jeon, BuIl (School of Electrical, Electronics and Communication Engineering, KOREATECH)
Kim, Jongwon (School of Electrical, Electronics and Communication Engineering, KOREATECH)
Publication Information
Journal of IKEEE / v.23, no.2, 2019 , pp. 727-734 More about this Journal
Abstract
This paper confirms whether the movement or specific operation of the muscles in the process of transferring a person from the brain can find a signal showing an essential feature of a certain part of the brain. As a rule, the occurrence of EEG(Electroencephalogram) changes when a signal is received from a specific action or from an induced action. These signals are very vague and difficult to distinguish from the naked eye. Therefore, it is necessary to define a signal for analysis before classification. The EEG form can be divided into the alpha, beta, delta, theta and gamma regions in the frequency ranges. The specific size of these signals does not reflect the exact behavior or intention, since the band or energy difference of the activated frequencies varies depending on the EEG measurement domain. However, if different actions are performed in a specific method, it is possible to classify the movement based on EEG activity and to determine the EEG tendency affecting the movement. Therefore, in this article, we first study the EEG expression pattern based on the activation of the left and right biceps EMG, and then we determine whether there is a significant difference between the EEG due to the activation of the left and right muscles through EEG. If we can find the EEG classification criteria in accordance with the EMG activation, it can help to understand the form of the transmitted signal in the process of transmitting signals from the brain to each muscle. In addition, we can use a lot of unknown EEG information through more complex types of brain signal generation in the future.
Keywords
EMG; EEG; signal analysis; user intention; Theta frequency;
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Times Cited By KSCI : 2  (Citation Analysis)
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