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• W2070291386 abstract "Recent development in cognitive neuroscience and brain imaging technologies provides us with a increasing ability to a new multidisciplinary research, brain machine interactions (BMIs). In this paper, the critical technologies used in BMIs, such as bio-sensor, translation algorithms, and the major applications are discussed. By providing an overview of these aspects, we can see how advanced technologies in these areas can be utilized to improve the state of art BMIs. In this paper, based on real EEG data, RBF neural network method and a machine learning algorithm, weighted locally linear embedding (WLLE) are proposed for neural modeling and pattern recognition respectively to efficiently interpret brain patterns for BMIs." @default.
• W2070291386 created "2016-06-24" @default.
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• W2070291386 date "2008-01-01" @default.
• W2070291386 modified "2023-09-22" @default.
• W2070291386 title "Methodologies on Brain-Machine Interaction" @default.
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• W2070291386 doi "https://doi.org/10.3182/20080706-5-kr-1001.02333" @default.
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