An approach for brain-controlled prostheses based on Scene Graph Steady-State Visual Evoked Potentials

Brain Research
Rui LiJiangcheng Chen

Abstract

Brain control technology can restore communication between the brain and a prosthesis, and choosing a Brain-Computer Interface (BCI) paradigm to evoke electroencephalogram (EEG) signals is an essential step for developing this technology. In this paper, the Scene Graph paradigm used for controlling prostheses was proposed; this paradigm is based on Steady-State Visual Evoked Potentials (SSVEPs) regarding the Scene Graph of a subject's intention. A mathematic model was built to predict SSVEPs evoked by the proposed paradigm and a sinusoidal stimulation method was used to present the Scene Graph stimulus to elicit SSVEPs from subjects. Then, a 2-degree of freedom (2-DOF) brain-controlled prosthesis system was constructed to validate the performance of the Scene Graph-SSVEP (SG-SSVEP)-based BCI. The classification of SG-SSVEPs was detected via the Canonical Correlation Analysis (CCA) approach. To assess the efficiency of proposed BCI system, the performances of traditional SSVEP-BCI system were compared. Experimental results from six subjects suggested that the proposed system effectively enhanced the SSVEP responses, decreased the degradation of SSVEP strength and reduced the visual fatigue in comparison with the traditional SSVE...Continue Reading

Citations

Oct 5, 2019·Journal of Neural Engineering·Yimin HouXiangmin Lun
Aug 31, 2020·Medical & Biological Engineering & Computing·Xiaodong ZhangAhmad Bala Alhassan
Jul 6, 2021·Frontiers in Neurorobotics·Xiaodong ZhangGui Yin

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