Objective. Transient visual evoked potential (TVEP) can reflect the condition of the visual pathway and has been widely used in brain–computer interface. TVEP signals are typically obtained by averaging the time-locked brain responses across dozens or even hundreds of stimulations, in order to remove different kinds of interferences. However, this procedure increases the time needed to detect the brain status in realistic applications. Meanwhile, long repeated stimuli can vary the evoked potentials and discomfort the subjects. Therefore, a novel unsupervised framework was developed in this study to realize the fast extraction of single-channel TVEP signals with a high signal-to-noise ratio. Approach. Using the principle of nonlinear aperiodic FitzHugh–Nagumo (FHN) model, a fast extraction and signal restoration technology of TVEP waveform based on FHN stochastic resonance is proposed to achieve high-quality acquisition of signal features with less average times. Results: A synergistic effect produced by noise, aperiodic signal and nonlinear system can force the energy of noise to be transferred into TVEP and hence amplifying the useful P100 feature while suppressing multi-scale noise. Significance. Compared with the conventional average and average-singular spectrum analysis-independent component analysis(average-SSA-ICA) method, the average-FHN method has a shorter stimulation time which can greatly improve the comfort of patients in clinical TVEP detection and a better performance of TVEP waveform i.e. a higher accuracy of P100 latency. The FHN recovery method is not only highly correlated with the original signal, but also can better highlight the P100 amplitude, which has high clinical application value.

目标。瞬态视觉诱发电位（TVEP）可以反映视觉通路的状况，已广泛应用于脑机接口。TVEP 信号通常是通过对数十甚至数百次刺激的时间锁定大脑反应进行平均来获得的，以消除不同类型的干扰。然而，此过程增加了在实际应用中检测大脑状态所需的时间。同时，长时间重复的刺激会改变诱发电位并使受试者感到不适。因此，本研究开发了一种新的无监督框架，以实现高信噪比的单通道 TVEP 信号的快速提取。方法。利用非线性非周期FitzHugh-Nagumo（FHN）模型的原理，提出了一种基于FHN随机共振的TVEP波形快速提取和信号恢复技术，以较少的平均次数实现高质量的信号特征采集。结果：噪声、非周期信号和非线性系统产生的协同效应可以迫使噪声能量转移到TVEP中，从而在抑制多尺度噪声的同时放大有用的P100特征。意义. 与传统的平均和平均奇异谱分析-独立成分分析（average-SSA-ICA）方法相比，average-FHN方法具有更短的刺激时间，可以大大提高患者在临床TVEP检测中的舒适度和更好的性能TVEP 波形，即更高的 P100 延迟精度。FHN恢复方法不仅与原始信号高度相关，而且能更好地突出P100幅度，具有较高的临床应用价值。