A Multi-Staged EEG (Electroencephalogram) Recognition Method
This paper is about EEG recognition method and system. In more details, it is about multi-staged EEG method and system that accurately enables the EEG of user by saving the EEG generated accordingly with the behavior of user and equipping and comparing personal database constructed through EEG data of individual and public database constructed through EEG similarity data of multiple number of people. Such EEG measurement system include EEG measurement sensor to detect EEG, EEG measurement register for registration of measured EEG, EEG database to save registered EEG, and comparison unit to compare saved EEG. In here, EEG measurement register is composed of classification unit that classifies EEG fingerprint accordingly with the trait of each individual, feature point classification unit to save it to EEG measurement database, and classification comparison unit to infer to behavior and thought of people based on feature point. Therefore, it has advantaged in that thought or behavioral trait of each individual can be inferred to through multi-stages primarily by comparing the feature point of EEG with the use of findings of this paper to infer similar behavior or thought and secondarily comparing the data constructed to the database. In this paper, EEG database was constructed in diverse situation in order to analyze qualitative and quantitative trait of EEG. In order to verify EEG measurement method using EEG traits and multi-staged EEG recognition method, Euclidean distance classifier, MAHALANOBIS distance classifier, and multi-staged EEG recognition method proposed in this study were used. With the experiment result of this study, it was verified that more accurate measurement can be conducted compared to previous EEG recognition method.
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Document Type: Research Article
Affiliations: Konyang University, Medical IT Engineering, #119 Daehang-ro, Nonsan, Chung-nam, South Korea
Publication date: April 1, 2017
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