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- W2809878388 abstract "This research aims to develop a method using an Electroencephalography (EEG) based brain-computer interface technology for enabling people to answer a true/false question by imagining to an answer in their mind; especially, for people with disabilities who cannot communicate with normal ways. Since, a single-electrode EEG is accurately method to recognize the internal state of mind. The acquisition of EEG signals on frontal electrode, which is pasted on the forehead between the left eye and hair (Fp1) from eight subjects for classification of mental task into two classes. The mental tasks were induced by showing images with symbol or text to allow the users reply a true/false question by imagination to an answer. The event related potential (ERPs) features were determined from the processed EEG signals for two classes of mental task. The acquired brain wave data were processed by the OpenViBE platform. Then, the classification was performed using LibSVM and Multiple-Layers Perceptron (MLP), while the parameters were differently validated with 10-Fold Cross Validation methods, and were compared for selection the highest accuracy of classification. The results show that the proposed method achieves 91% on maximum in accuracy." @default.
- W2809878388 created "2018-07-10" @default.
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- W2809878388 date "2018-06-27" @default.
- W2809878388 modified "2023-09-27" @default.
- W2809878388 title "Brain Wave Pattern Recognition of Two-Task Imagination by Using Single-Electrode EEG" @default.
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- W2809878388 doi "https://doi.org/10.1007/978-3-319-93692-5_19" @default.
- W2809878388 hasPublicationYear "2018" @default.
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