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arXiv · 1707.07233

Brain Computer Interface for Gesture Control of a Social Robot: an Offline Study

Reza Abiri·Griffin Heise·Xiaopeng Zhao·Yang Jiang·Fateme Abiri
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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.

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Reza Abiri, Griffin Heise, Xiaopeng Zhao, Yang Jiang, Fateme Abiri. 2017-07-23. Brain Computer Interface for Gesture Control of a Social Robot: an Offline Study. https://arxiv.org/abs/1707.07233

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