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基于知识图谱的稳态视觉诱发电位脑机接口虚拟现实立体刺激参数优化

Optimization of SSVEP-BCI Virtual Reality Stereo Stimulation Parameters Based on Knowledge Graph.

作者信息

Zhu Shixuan, Yang Jingcheng, Ding Peng, Wang Fan, Gong Anmin, Fu Yunfa

机构信息

School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650032, China.

Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming 650032, China.

出版信息

Brain Sci. 2023 Apr 24;13(5):710. doi: 10.3390/brainsci13050710.

DOI:10.3390/brainsci13050710
PMID:37239182
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10216479/
Abstract

The steady-state visually evoked potential (SSVEP) is an important type of BCI that has various potential applications, including in virtual environments using virtual reality (VR). However, compared to VR research, the majority of visual stimuli used in the SSVEP-BCI are plane stimulation targets (PSTs), with only a few studies using stereo stimulation targets (SSTs). To explore the parameter optimization of the SSVEP-BCI virtual SSTs, this paper presents a parameter knowledge graph. First, an online VR stereoscopic stimulation SSVEP-BCI system is built, and a parameter dictionary for VR stereoscopic stimulation parameters (shape, color, and frequency) is established. The online experimental results of 10 subjects under different parameter combinations were collected, and a knowledge graph was constructed to optimize the SST parameters. The best classification performances of the shape, color, and frequency parameters were sphere (91.85%), blue (94.26%), and 13Hz (95.93%). With various combinations of virtual reality stereo stimulation parameters, the performance of the SSVEP-BCI varies. Using the knowledge graph of the stimulus parameters can help intuitively and effectively select appropriate SST parameters. The knowledge graph of the stereo target stimulation parameters presented in this work is expected to offer a way to convert the application of the SSVEP-BCI and VR.

摘要

稳态视觉诱发电位（SSVEP）是脑机接口的一种重要类型，具有多种潜在应用，包括在使用虚拟现实（VR）的虚拟环境中。然而，与VR研究相比，SSVEP脑机接口中使用的大多数视觉刺激是平面刺激目标（PST），只有少数研究使用立体刺激目标（SST）。为了探索SSVEP脑机接口虚拟SST的参数优化，本文提出了一个参数知识图谱。首先，构建了一个在线VR立体刺激SSVEP脑机接口系统，并建立了VR立体刺激参数（形状、颜色和频率）的参数字典。收集了10名受试者在不同参数组合下的在线实验结果，并构建了一个知识图谱来优化SST参数。形状、颜色和频率参数的最佳分类性能分别为球体（91.85%）、蓝色（94.26%）和13Hz（95.93%）。随着虚拟现实立体刺激参数的各种组合，SSVEP脑机接口的性能会有所不同。使用刺激参数的知识图谱可以帮助直观有效地选择合适的SST参数。本文提出的立体目标刺激参数知识图谱有望为SSVEP脑机接口与VR的应用转换提供一种途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/c69fcae7b4e9/brainsci-13-00710-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/a865ed65a237/brainsci-13-00710-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/5ef414f3cb48/brainsci-13-00710-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/fe3044575b1a/brainsci-13-00710-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/8fdde35cc105/brainsci-13-00710-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/fc05d12e44c8/brainsci-13-00710-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/8825cb4bc4e7/brainsci-13-00710-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/a3963f01534e/brainsci-13-00710-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/568b5b410b25/brainsci-13-00710-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/1c3868a61b07/brainsci-13-00710-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/c69fcae7b4e9/brainsci-13-00710-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/a865ed65a237/brainsci-13-00710-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/5ef414f3cb48/brainsci-13-00710-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/fe3044575b1a/brainsci-13-00710-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/8fdde35cc105/brainsci-13-00710-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/fc05d12e44c8/brainsci-13-00710-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/8825cb4bc4e7/brainsci-13-00710-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/a3963f01534e/brainsci-13-00710-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/568b5b410b25/brainsci-13-00710-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/1c3868a61b07/brainsci-13-00710-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/332a/10216479/c69fcae7b4e9/brainsci-13-00710-g010.jpg

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