A sub-region combination scheme for spatial coding in a high-frequency SSVEP-based BCI.

IF 3.7 3区 医学 Q2 ENGINEERING, BIOMEDICAL Journal of neural engineering Pub Date : 2023-07-27 DOI:10.1088/1741-2552/ace8bd
Ruochen Hu, Gege Ming, Yijun Wang, Xiaorong Gao
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Abstract

Objective.In studying the spatial coding mechanism of visual evoked potentials, it is significant to construct a model that shows the relationship between steady-state visual evoked potential (SSVEP) responses to the local and global visual field stimulation. In order to investigate whether SSVEPs produced by sub-region stimulation can predict that produced by joint region stimulation, a sub-region combination scheme for spatial coding in a high-frequency SSVEP-based brain-computer interface (BCI) is developed innovatively.Approach.An annular visual field is divided equally into eight sub-regions. The 60 Hz visual stimuli in different sub-regions and joint regions are presented separately to participants. The SSVEP produced by the sub-region stimulation is superimposed to simulate the SSVEP produced by the joint region stimulation with different spatial combinations. A four-class spatially-coded BCI paradigm is used to evaluate the simulated classification performance, and the performance ranking of all simulated SSVEPs is obtained. Six representative stimulus patterns from two performance levels and three stimulus areas are applied to the online BCI system for each participant.Main results.The experimental result shows that the proposed scheme can implement a spatially-coded visual BCI system and realize satisfactory performance with imperceptible flicker. Offline analysis indicates that the classification accuracy and information transfer rate (ITR) are 89.69 ± 8.75% and 24.35 ± 7.09 bits min-1with 3 s data length under the 3/8 stimulus area. The online BCI system reaches an average classification accuracy of 87.50 ± 9.13% with 3 s data length, resulting in an ITR of 22.48 ± 6.71 bits min-1under the 3/8 stimulus area.Significance.This study proves the feasibility of using the sub-region's response to predict the joint region's response. It has the potential to extend to other frequency bands and lays a foundation for future research on more complex spatial coding methods.

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基于ssvep的高频脑机接口空间编码的子区域组合方案。
目标。在研究视觉诱发电位的空间编码机制中,建立稳态视觉诱发电位(SSVEP)响应局部和全局视野刺激的关系模型具有重要意义。为了研究子区域刺激产生的ssvep是否能预测联合区域刺激产生的ssvep,创新性地提出了一种基于高频ssvep的脑机接口(BCI)空间编码的子区域组合方案。不同子区域和关节区域的60 Hz视觉刺激分别呈现给被试。将子区域刺激产生的SSVEP进行叠加,模拟不同空间组合的联合区域刺激产生的SSVEP。采用四类空间编码BCI范式对模拟的分类性能进行了评价,得到了所有模拟的ssvep的性能排名。从两个表现水平和三个刺激区域中选取六种具有代表性的刺激模式应用于每个参与者的在线BCI系统。主要的结果。实验结果表明,该方案能够实现空间编码的视觉BCI系统,并在闪烁不明显的情况下实现令人满意的性能。离线分析表明,在3/8刺激区域下,当数据长度为3 s时,分类准确率为89.69±8.75%,信息传输率(ITR)为24.35±7.09 bits min-1。该在线BCI系统在数据长度为3 s的情况下,平均分类准确率达到87.50±9.13%,在3/8刺激区域下的ITR为22.48±6.71 bits min-1。它具有扩展到其他频段的潜力,为未来更复杂的空间编码方法的研究奠定了基础。
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来源期刊
Journal of neural engineering
Journal of neural engineering 工程技术-工程:生物医学
CiteScore
7.80
自引率
12.50%
发文量
319
审稿时长
4.2 months
期刊介绍: The goal of Journal of Neural Engineering (JNE) is to act as a forum for the interdisciplinary field of neural engineering where neuroscientists, neurobiologists and engineers can publish their work in one periodical that bridges the gap between neuroscience and engineering. The journal publishes articles in the field of neural engineering at the molecular, cellular and systems levels. The scope of the journal encompasses experimental, computational, theoretical, clinical and applied aspects of: Innovative neurotechnology; Brain-machine (computer) interface; Neural interfacing; Bioelectronic medicines; Neuromodulation; Neural prostheses; Neural control; Neuro-rehabilitation; Neurorobotics; Optical neural engineering; Neural circuits: artificial & biological; Neuromorphic engineering; Neural tissue regeneration; Neural signal processing; Theoretical and computational neuroscience; Systems neuroscience; Translational neuroscience; Neuroimaging.
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