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• W2621100405 abstract "A novel hybrid brain-computer interface (BCI) based on the electroencephalogram (EEG) signal which consists of a motor imagery- (MI-) based online interactive brain-controlled switch, “teeth clenching” state detector, and a steady-state visual evoked potential- (SSVEP-) based BCI was proposed to provide multidimensional BCI control. MI-based BCI was used as single-pole double throw brain switch (SPDTBS). By combining the SPDTBS with 4-class SSEVP-based BCI, movement of robotic arm was controlled in three-dimensional (3D) space. In addition, muscle artifact (EMG) of “teeth clenching” condition recorded from EEG signal was detected and employed as interrupter, which can initialize the statement of SPDTBS. Real-time writing task was implemented to verify the reliability of the proposed noninvasive hybrid EEG-EMG-BCI. Eight subjects participated in this study and succeeded to manipulate a robotic arm in 3D space to write some English letters. The mean decoding accuracy of writing task was <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M1><mml:mn fontstyle=italic>0.93</mml:mn><mml:mo>±</mml:mo><mml:mn fontstyle=italic>0.03</mml:mn></mml:math>. Four subjects achieved the optimal criteria of writing the word “HI” which is the minimum movement of robotic arm directions (15 steps). Other subjects had needed to take from 2 to 4 additional steps to finish the whole process. These results suggested that our proposed hybrid noninvasive EEG-EMG-BCI was robust and efficient for real-time multidimensional robotic arm control." @default.
• W2621100405 created "2017-06-09" @default.
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• W2621100405 date "2017-01-01" @default.
• W2621100405 modified "2023-10-18" @default.
• W2621100405 title "Noninvasive Electroencephalogram Based Control of a Robotic Arm for Writing Task Using Hybrid BCI System" @default.
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• W2621100405 doi "https://doi.org/10.1155/2017/8316485" @default.
• W2621100405 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5474280" @default.
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