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Study of the Home-Auxiliary Robot Based on BCI

School of Mechanic Engineering, Northeast Electric Power University, Jilin 132012, China
College of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China
Author to whom correspondence should be addressed.
Sensors 2018, 18(6), 1779;
Received: 31 March 2018 / Revised: 20 May 2018 / Accepted: 29 May 2018 / Published: 1 June 2018
(This article belongs to the Special Issue Sensors for Biosignal Processing)
A home-auxiliary robot platform is developed in the current study which could assist patients with physical disabilities and older persons with mobility impairments. The robot, mainly controlled by brain computer interface (BCI) technology, can not only perform actions in a person’s field of vision, but also work outside the field of vision. The wavelet decomposition (WD) is used in this study to extract the δ (0~4 Hz) and θ (4~8 Hz) sub-bands of subjects’ electroencephalogram (EEG) signals. The correlation between pairs of 14 EEG channels is determined with synchronization likelihood (SL), and the brain network structure is generated. Then, the motion characteristics are analyzed using the brain network parameters clustering coefficient (C) and global efficiency (G). Meanwhile, the eye movement characteristics in the F3 and F4 channels are identified. Finally, the motion characteristics identified by brain networks and eye movement characteristics can be used to control the home-auxiliary robot platform. The experimental result shows that the accuracy rate of left and right motion recognition using this method is more than 93%. Additionally, the similarity between that autonomous return path and the real path of the home-auxiliary robot reaches up to 0.89. View Full-Text
Keywords: home-auxiliary robot platform; physical disabilities; BCI; SL; autonomous return home-auxiliary robot platform; physical disabilities; BCI; SL; autonomous return
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MDPI and ACS Style

Wang, F.; Zhang, X.; Fu, R.; Sun, G. Study of the Home-Auxiliary Robot Based on BCI. Sensors 2018, 18, 1779.

AMA Style

Wang F, Zhang X, Fu R, Sun G. Study of the Home-Auxiliary Robot Based on BCI. Sensors. 2018; 18(6):1779.

Chicago/Turabian Style

Wang, Fuwang, Xiaolei Zhang, Rongrong Fu, and Guangbin Sun. 2018. "Study of the Home-Auxiliary Robot Based on BCI" Sensors 18, no. 6: 1779.

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