Zheng Xiaowei, Wei Xin, Xu Guanghua, Zhang Rui
School of Mathematics, Northwest University, Xi'an, China.
Medical Big Data Research Center, Northwest University, Xi'an, China.
Cogn Neurodyn. 2024 Aug;18(4):1641-1650. doi: 10.1007/s11571-023-10036-2. Epub 2023 Dec 1.
This study aimed to explore the effect of various noise definition criteria in linear extrapolation technique to noise level baseline on steady-state visual evoked potential (SSVEP)-based visual acuity assessment. Four noise definition criteria on frequency-domain, i.e., the mean amplitude at the two adjacent bins of the target frequency, the mean amplitude of a narrow frequency band on either side of the target frequency, the mean amplitude at a broad frequency band except for the target frequency and its harmonic frequencies, and the mean amplitude at a broad frequency band at resting state, corresponding to noise 1, noise 2, noise 3, and noise 4, were introduced to calculate noise level baselines. Then, two experiments were implemented. In experiment 1, electroencephalography (EEG) signals of resting state were recorded for fourteen subjects. In experiment 2, the visual stimuli of vertical sinusoidal gratings at six spatial frequency steps were used to induce SSVEPs for twelve subjects. Finally, SSVEP visual acuity was obtained via the SSVEP visual acuity threshold estimation of linear extrapolation technique to noise level baseline with various noise definition criteria. The bland-Altman analysis found that the difference between subjective Freiburg Visual Acuity and Contrast Test (FrACT) and objective SSVEP visual acuity was - 0.0892, - 0.1071, - 0.0745, and - 0.0804 logMAR and the 95% limit of agreement was 0.2150, 0.2146, 0.2046, and 0.2189 logMAR for noise 1, noise 2, noise 3, and noise 4, respectively, indicating that visual acuity of noise 3 definition criterion, i.e., the mean amplitude at a broad frequency band except for the target frequency and its harmonic frequencies, showed the best performance. This study recommended noise definition criterion 3 of the mean amplitude at a broad frequency band to calculate the noise level baseline in the linear extrapolation of SSVEP-based visual acuity assessment.
本研究旨在探讨线性外推技术中各种噪声定义标准对基于稳态视觉诱发电位(SSVEP)的视力评估中噪声水平基线的影响。引入了频域上的四种噪声定义标准,即目标频率两个相邻频段的平均幅度、目标频率两侧窄频带的平均幅度、除目标频率及其谐波频率外的宽频带的平均幅度以及静息状态下宽频带的平均幅度,分别对应噪声1、噪声2、噪声3和噪声4,用于计算噪声水平基线。然后,进行了两个实验。在实验1中,记录了14名受试者静息状态下的脑电图(EEG)信号。在实验2中,使用六个空间频率步长的垂直正弦光栅视觉刺激,对12名受试者诱发SSVEP。最后,通过线性外推技术对噪声水平基线采用各种噪声定义标准进行SSVEP视力阈值估计,获得SSVEP视力。布兰德-奥特曼分析发现,主观弗赖堡视力与对比度测试(FrACT)和客观SSVEP视力之间的差异分别为-0.0892、-0.1071、-0.0745和-0.0804 logMAR,噪声1、噪声2、噪声3和噪声4的95%一致性界限分别为0.2150、0.2146、0.2046和0.2189 logMAR,这表明噪声3定义标准,即除目标频率及其谐波频率外的宽频带的平均幅度,表现最佳。本研究推荐在基于SSVEP的视力评估的线性外推中,采用宽频带平均幅度的噪声定义标准3来计算噪声水平基线。