脑电脑接口的双模式视觉系统:集成SSVEP和P300响应
Ekgari Kasawala1, Surej Mouli1
1Engineering for Health Research Group, Biomedical Engineering, Aston University, Aston Street, Birmingham B4 7ET, UK.
Sensors (Basel, Switzerland)
|April 28, 2025
概括
这项研究引入了一种新的脑计算机接口 (BCI),使用发光二极管 (LED) 刺激来结合稳定状态视觉唤起潜能 (SSVEP) 和P300反应. 混合系统实现了86.25%的精度和42.08比特/分钟的信息传输速率用于设备控制.
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:
- 大脑-计算机接口 (BCI) 通常使用稳态视觉唤起潜能 (SSVEP) 和P300响应来控制设备.
- 目前的BCI系统通常依赖于液晶显示器 (LCD) 技术,限制了实际应用.
- 需要改进的BCI系统,以更高的准确性和实际可用性.
研究的目的:
- 为BCI开发和评估一种基于发光二极管 (LED) 的新型双刺激装置.
- 通过整合SSVEP和P300范式来提高SSVEP分类的准确性.
- 在分类准确性和信息传输速率 (ITR) 方面评估混合系统的性能.
主要方法:
- 开发了一种基于LED的双刺激装置,使用四种不同的频率 (7-10 Hz) 进行方向控制.
- 采用实时特征提取通过快速里埃变换 (FFT) 振幅和P300峰值检测.
- 经过验证的刺激频率精度使用示波器测量.
- 实现了一个信号处理算法来区分刺激频率并与P300事件标记器相关联.
主要成果:
- LED刺激硬件的频率偏差是最小的 (0.15% - 0.20%).
- 信号处理算法成功地区分了所有四种刺激频率及其P300标记.
- 混合BCI系统实现了平均分类准确率为86.25%.
- 该系统显示平均信息传输速率 (ITR) 为每分钟42.08位 (bpm).
结论:
- 这种基于LED的新型双刺激装置有效地整合了SSVEP和P300模式,用于BCI.
- 混合系统显著超过传统BCI准确度值 (70%).
- 这种方法为实际和高性能BCI应用提供了有前途的进步.
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