A high-frequency SSVEP-BCI system based on a 360 Hz refresh rate.

IF 3.7 3区 医学 Q2 ENGINEERING, BIOMEDICAL Journal of neural engineering Pub Date : 2023-08-31 DOI:10.1088/1741-2552/acf242
Ke Liu, Zhaolin Yao, Li Zheng, Qingguo Wei, Weihua Pei, Xiaorong Gao, Yijun Wang
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Abstract

Objective. Steady-state visual evoked potential (SSVEP) based brain-computer interfaces (BCIs) often struggle to balance user experience and system performance. To address this challenge, this study employed stimuli in the 55-62.8 Hz frequency range to implement a 40-target BCI speller that offered both high-performance and user-friendliness.Approach. This study proposed a method that presents stable multi-target stimuli on a monitor with a 360 Hz refresh rate. Real-time generation of stimulus matrix and stimulus rendering was used to ensure stable presentation while reducing the computational load. The 40 targets were encoded using the joint frequency and phase modulation method, offline and online BCI experiments were conducted on 16 subjects using the task discriminant component analysis algorithm for feature extraction and classification.Main results. The online BCI system achieved an average accuracy of 88.87% ± 3.05% and an information transfer rate of 51.83 ± 2.77 bits min-1under the low flickering perception condition.Significance. These findings suggest the feasibility and significant practical value of the proposed high-frequency SSVEP BCI system in advancing the visual BCI technology.

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基于360 Hz刷新率的高频SSVEP-BCI系统。
目标。基于稳态视觉诱发电位(SSVEP)的脑机接口(bci)常常难以平衡用户体验和系统性能。为了解决这一挑战,本研究采用55-62.8 Hz频率范围内的刺激来实现一个具有40个目标的BCI拼写器,该方法提供了高性能和用户友好性。本研究提出了一种在360赫兹刷新率的显示器上呈现稳定的多目标刺激的方法。采用刺激矩阵的实时生成和刺激渲染,保证了呈现的稳定性,同时减少了计算量。采用频率与相位联合调制的方法对40个目标进行编码,采用任务判别成分分析算法对16个被试进行离线和在线脑机接口实验进行特征提取和分类。主要的结果。在低闪烁感知条件下,在线BCI系统的平均准确率为88.87%±3.05%,信息传输率为51.83±2.77 bits min-1。这些结果表明所提出的高频SSVEP脑机接口系统在推进视觉脑机接口技术方面的可行性和重要的实用价值。
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来源期刊
Journal of neural engineering
Journal of neural engineering 工程技术-工程:生物医学
CiteScore
7.80
自引率
12.50%
发文量
319
审稿时长
4.2 months
期刊介绍: The goal of Journal of Neural Engineering (JNE) is to act as a forum for the interdisciplinary field of neural engineering where neuroscientists, neurobiologists and engineers can publish their work in one periodical that bridges the gap between neuroscience and engineering. The journal publishes articles in the field of neural engineering at the molecular, cellular and systems levels. The scope of the journal encompasses experimental, computational, theoretical, clinical and applied aspects of: Innovative neurotechnology; Brain-machine (computer) interface; Neural interfacing; Bioelectronic medicines; Neuromodulation; Neural prostheses; Neural control; Neuro-rehabilitation; Neurorobotics; Optical neural engineering; Neural circuits: artificial & biological; Neuromorphic engineering; Neural tissue regeneration; Neural signal processing; Theoretical and computational neuroscience; Systems neuroscience; Translational neuroscience; Neuroimaging.
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