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• W2963626267 abstract "Brain computer interface (BCI) provides promising applications in neuroprosthesis and neurorehabilitation by controlling computers and robotic devices based on the patient's intentions. Here, we have developed a novel BCI platform that controls a personalized social robot using noninvasively acquired brain signals. Scalp electroencephalogram (EEG) signals are collected from a user in real-time during tasks of imaginary movements. The imagined body kinematics are decoded using a regression model to calculate the user-intended velocity. Then, the decoded kinematic information is mapped to control the gestures of a social robot. The platform here may be utilized as a human-robot-interaction framework by combining with neurofeedback mechanisms to enhance the cognitive capability of persons with dementia." @default.
• W2963626267 created "2019-07-30" @default.
• W2963626267 creator A5011600733 @default.
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• W2963626267 date "2017-05-01" @default.
• W2963626267 modified "2023-09-23" @default.
• W2963626267 title "Brain computer interface for gesture control of a social robot: An offline study" @default.
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• W2963626267 doi "https://doi.org/10.1109/iraniancee.2017.7985231" @default.
• W2963626267 hasPublicationYear "2017" @default.
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