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通过二进制编码的闪刺激,通过人工智能驱动的瞳孔-计算机接口
1Next-generation Mechanical Design Laboratory, Korea University, Seoul, 04763, Republic of Korea.
Computers in biology and medicine
|September 18, 2025
概括
一个新的瞳孔-计算机接口 (PCI) 使用瞳孔对光变化的反应来进行交互. 这种由人工智能驱动的系统提供了高精度和信息传输速率,为传统硬件提供了稳定,低训练的替代方案.
科学领域:
- 人与计算机的交互
- 生物医学工程 生物医学工程
- 人工智能的人工智能
背景情况:
- 传统的脑电脑接口通常需要广泛的用户培训和专门的硬件.
- 对视觉刺激的瞳孔反应,称为瞳孔光反射 (PLR),提供了一个潜在的交互替代方案.
- 现有的基于PLR的接口在性能和复杂性方面面临限制.
研究的目的:
- 开发和评估一种利用人工智能提高性能的新型瞳孔-计算机接口 (PCI).
- 为了克服现有的基于脑电图的硬件的局限性,使用学生信号分析.
- 评估拟议的PCI系统的分类准确性和信息传输率 (ITR).
主要方法:
- 使用人工智能设计了一种新的PCI系统,用于模拟学生尺寸变化.
- 对参与者展示了具有不同亮度的二进制编码视觉刺激.
- 基于卷积神经网络 (CNN) 的深度学习被用于信号模式分类.
- 实验对12名健康受试者进行了实验,使用4级,10级和20级刺激.
主要成果:
- 拟议的PCI系统实现了高分类精度:91.84% (20级),93.84% (10级) 和98.61% (4级).
- 信息传输速度 (ITR) 达到59.74比特/分钟 (20级),62.04比特/分钟 (10级) 和69.36比特/分钟 (4级).
- 性能明显优于之前基于PLR的接口研究.
结论:
- 开发的PCI系统提供了一个简单,经济高效,低培训的接口解决方案.
- 该系统表现出高精度和ITR,使其成为人机交互的可行替代方案.
- 拟议的PCI保持了长期稳定性,并且需要最低限度的用户培训.
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