Mouli Surej, Palaniappan Ramaswamy
Data Science Research Group, School of Computing, University of Kent.
HardwareX. 2020 May 22;8:e00113. doi: 10.1016/j.ohx.2020.e00113. eCollection 2020 Oct.
A fully customisable chip-on board (COB) LED design to evoke two brain responses simultaneously (steady state visual evoked potential (SSVEP) and transient evoked potential, P300) is discussed in this paper. Considering different possible modalities in brain-computer interfacing (BCI), SSVEP is widely accepted as it requires a lesser number of electroencephalogram (EEG) electrodes and minimal training time. The aim of this work was to produce a hybrid BCI hardware platform to evoke SSVEP and P300 precisely with reduced fatigue and improved classification performance. The system comprises of four independent radial green visual stimuli controlled individually by a 32-bit microcontroller platform to evoke SSVEP and four red LEDs flashing at random intervals to generate P300 events. The system can also record the P300 event timestamps that can be used in classification, to improve the accuracy and reliability. The hybrid stimulus was tested for real-time classification accuracy by controlling a LEGO robot to move in four directions.
本文讨论了一种完全可定制的板载芯片（COB）LED设计，该设计可同时诱发两种脑电反应（稳态视觉诱发电位（SSVEP）和瞬态诱发电位P300）。考虑到脑机接口（BCI）中不同的可能模式，SSVEP被广泛接受，因为它需要较少数量的脑电图（EEG）电极且训练时间最短。这项工作的目的是制造一个混合BCI硬件平台，以精确诱发SSVEP和P300，同时减少疲劳并提高分类性能。该系统由四个独立的径向绿色视觉刺激组成，由一个32位微控制器平台单独控制以诱发SSVEP，还有四个红色LED以随机间隔闪烁以产生P300事件。该系统还可以记录可用于分类的P300事件时间戳，以提高准确性和可靠性。通过控制乐高机器人向四个方向移动，对混合刺激进行了实时分类准确性测试。
