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Updated: Sep 8, 2026
Combining Computer Game-Based Behavioural Experiments With High-Density EEG and Infrared Gaze Tracking
Published on: December 16, 2010
A high-rate 480-target hybrid BCI system based on SSVEP and sEMG
Zexin Pang1, Zhaohui Li1, Xinying Xie1
1State Key Laboratory of Advanced Medical Materials and Devices, Tianjin Key Laboratory of Neuromodulation and Neurorepair, Institute of Biomedical Engineering, Tianjin Institutes of Health Science, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China.
Abstract:
In the field of brain-computer interfaces (BCIs), a sufficiently high information transfer rate (ITR) serves as the prerequisite guarantee for the realization of practical application of electroencephalography (EEG)-based BCIs. Hybrid BCIs combining multiple biosignals with EEG can broaden the command set and improve ITR. We propose a hybrid BCI system combining surface electromyography (sEMG) and steady-state visual evoked potential (SSVEP), which utilizes 120 flicker frequencies and 4 gesture movements to encode 480 targets. Moreover, high-density electrodes are used to acquire more EEG information. In the online experiment, the average classification accuracy achieved 84.55 ± 7.23%, with an average ITR of 260.07 ± 30.41 bits/min. In this study, an advanced high-performance hybrid BCI system is constructed. The size of command set of the proposed system is nearly identical to that of the state-of-the-art system with the maximum number of targets, and its performance also ranks among the top tier. This research provides technical advancements and a valuable reference for the implementation of BCI systems with large command sets.
