FPGA Implementation of Visual Noise Optimized Online Steady-State Motion Visual Evoked Potential BCI System*

Yanjun Zhang, Jun Xie, Guanghua Xu, Peng Fang, Guiling Cui, Guanglin Li, Guozhi Cao, Tao Xue, Xiaodong Zhang, Min Li, T. Tao
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引用次数: 1

Abstract

In order to improve the practicability of brain computer interface (BCI) system based on steady-state visual evoked potential (SSVEP), it is necessary to design BCI equipment with portability and low-cost. According to the principle of stochastic resonance (SR), the recognition accuracy of visual evoked potential could be improved by full-screen visual noise. Based on the above requirements, this paper proposed the usage of field programmable gate array (FPGA) to control stimulator through high definition multimedia interface (HDMI) for the display of steady-state motion visual evoked potential (SSMVEP) paradigm. By adding spatially localized visual noise to the motion-reversal checkerboard paradigm, the recognition accuracy is improved. According to the experimental results under different noise levels, the average recognition accuracies calculated with occipital electrodes O1, Oz, O2, PO3, POz and PO4 are 77.2%, 87.5%, and 85.2% corresponding to noise standard deviations values of 0, 24, and 40, respectively. In order to analyze the SR effect on the recognition accuracy with utilization of spatially localized visual noise, statistical analyses on the recognition accuracies under different noise intensities and different channel combinations are carried out. Results showed that the spatially localized visual noise could significantly improve the recognition accuracy and the stability of the proposed FPGA based online SSMVEP BCI system.
视觉噪声优化在线稳态运动视觉诱发电位系统的FPGA实现*
为了提高基于稳态视觉诱发电位(SSVEP)的脑机接口(BCI)系统的实用性,有必要设计便携、低成本的脑机接口设备。根据随机共振原理,采用全屏视觉噪声可以提高视觉诱发电位的识别精度。基于上述要求,本文提出了利用现场可编程门阵列(FPGA)通过高清多媒体接口(HDMI)控制刺激器实现稳态运动视觉诱发电位(SSMVEP)显示的范式。通过在运动反转棋盘模式中加入空间局部视觉噪声,提高了识别精度。根据不同噪声水平下的实验结果,枕电极O1、Oz、O2、PO3、POz和PO4在噪声标准差值为0、24和40时的平均识别准确率分别为77.2%、87.5%和85.2%。为了分析SR对空间定位视觉噪声识别精度的影响,对不同噪声强度和不同信道组合下的识别精度进行了统计分析。结果表明,空间局部化的视觉噪声能够显著提高基于FPGA的在线SSMVEP BCI系统的识别精度和稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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