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Updated: May 24, 2025

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
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高频SSVEP-BCI与行列双频编码和解码策略,以减少训练数据.

Yufeng Ke, Xiaohe Chen, Wei Xu

    IEEE journal of biomedical and health informatics
    |March 3, 2025
    PubMed
    概括

    这项研究引入了一种新的高频稳态视觉唤起潜能 (SSVEP) 大脑计算机接口 (BCI) 使用双频方法. 这种方法允许使用最少的训练数据进行多个命令,以获得更舒适的用户体验.

    科学领域:

    • 神经科学是一个神经科学.
    • 生物医学工程 生物医学工程
    • 人与计算机的交互

    背景情况:

    • 基于稳态视觉唤起潜能 (SSVEP) 的脑计算机接口 (BCI) 提供了高精度和信息传输速率 (ITR).
    • 高频 (HF) 视觉刺激可以减少视觉疲劳,并提高SSVEP-BCI中的用户舒适度.
    • 当前的HF-SSVEP-BCI通常具有有限的指挥选项,并且需要大量的训练数据.

    研究的目的:

    • 开发一个舒适的BCI系统,支持多个命令,降低训练成本.
    • 提出一种使用高频刺激的新型行列双频编码和解码方法.
    • 为了提高用户的舒适性和减少SSVEP-BCI系统的培训要求.

    主要方法:

    • 实施了一种行列双频编码策略,其中20个目标排列在5x4矩阵中.
    • 每个目标都使用左和右场刺激,对行和列进行独特的频率相组合.
    • 来自共享行/列的脑电图 (EEG) 数据被用来训练一个集体解码模型.

    主要成果:

    • 使用自适应窗口方法评估了在线20个目标异步机器人手臂控制系统.
    • 该系统实现了105.14±14.15比特/分钟的高ITR,每个目标只有四次训练试验.

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  • 记录了优秀的性能指标:98.18 ± 2.87%的真实阳性率,7.39 ± 6.73%的假阳性率和91.88 ± 5.75%的准确性.

    • 结论:

    • 拟议的双频协议可以为SSVEP-BCI提供准确和快速的命令输出.
    • 这种方法显著减少了对广泛的个人培训数据的需求,并且使用的频率更少.
    • 开发的系统提供了一个更舒适和高效的BCI体验,具有多个指挥功能.