A multi-target brain-computer based on code modulated visual evoked potentials

The number of selectable targets is one of the main factors that affect the performance of a brain-computer interface (BCI). Most existing code modulated visual evoked potential (c-VEP) based BCIs use a single pseudorandom binary sequence and its circularly shifting sequences to modulate different stimulus targets, making the number of selectable targets limited by the length of modulation codes. This paper proposes a novel paradigm for c-VEP BCIs, which divides the stimulus targets into four target groups and each group of targets are modulated by a unique pseudorandom binary code and its circularly shifting codes. Based on the paradigm, a four-group c-VEP BCI with a total of 64 stimulus targets was developed and eight subjects were recruited to participate in the BCI experiment. Based on the experimental data, the characteristics of the c-VEP BCI were explored by the analyses of auto- and cross-correlation, frequency spectrum, signal to noise ratio and correlation coefficient. On the ...可选择靶标数量是影响脑机接口（brain-computer interface, BCI）性能的核心因素之一。当前绝大多数基于编码调制视觉诱发电位（code modulated visual evoked potential, c-VEP）的脑机接口，均采用单一伪随机二进制序列及其循环移位序列对不同刺激靶标进行调制，使得可选择靶标数量受限于调制码的长度。本文提出一种面向c-VEP脑机接口的新型范式：将刺激靶标划分为四组靶标集群，每组靶标均由一组独特的伪随机二进制码及其循环移位码进行调制。基于该范式，我们搭建了一套总共有64个刺激靶标的四分组c-VEP脑机接口系统，并招募8名受试者参与该脑机接口实验。基于实验采集的数据，我们通过自相关与互相关分析、频谱分析、信噪比分析以及相关系数分析，探究了该c-VEP脑机接口的信号特性。On the ...