Toward Brain-Actuated Humanoid Robots: Asynchronous Direct Control Using an EEG-Based BCI

The brain-computer interface (BCI) technique is a novel control interface to translate human intentions into appropriate motion commands for robotic systems. The aim of this study is to apply an asynchronous direct-control system for humanoid robot navigation using an electroencephalograph (EEG), based active BCI. The experimental procedures consist of offline training, online feedback testing, and real-time control sessions. The amplitude features from EEGs are extracted using power spectral analysis, while informative feature components are selected based on the Fisher ratio. The two classifiers are hierarchically structured to identify human intentions and trained to build an asynchronous BCI system. For the performance test, five healthy subjects controlled a humanoid robot navigation to reach a target goal in an indoor maze by using their EEGs based on real-time images obtained from a camera on the head of the robot. The experimental results showed that the subjects successfully controlled the humanoid robot in the indoor maze and reached the goal by using the proposed asynchronous EEG-based active BCI system.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2012-10
Language
ENG
Keywords

COMPUTER INTERFACE BCI; MOTOR IMAGERY; MOVEMENT SIGNAL; COMMUNICATION; NAVIGATION; CLASSIFICATION; SELECTION; RECOGNITION; TECHNOLOGY; NEURONS

Citation

IEEE TRANSACTIONS ON ROBOTICS, v.28, no.5, pp.1131 - 1144

ISSN
1552-3098
DOI
10.1109/TRO.2012.2201310
URI
http://hdl.handle.net/10203/66148
Appears in Collection
BiS-Journal Papers(저널논문)CS-Journal Papers(저널논문)
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