The steady-state visual evoked potential (SSVEP) is one of the most widely used modalities in brain-computer interfaces (BCIs) due to its many advantages. However, the existence of harmonics and the limited range of responsive frequencies in SSVEP make it challenging to further expand the number of targets without sacrificing other aspects of the interface or putting additional constraints on the system. This paper introduces a novel multi-frequency stimulation method for SSVEP and investigates its potential to effectively and efficiently increase the number of targets presented. The proposed stimulation method, obtained by the superposition of the stimulation signals at different frequencies, is size-efficient, allows single-step target identification, puts no strict constraints on the usable frequency range, can be suited to self-paced BCIs, and does not require specific light sources. In addition to the stimulus frequencies and their harmonics, the evoked SSVEP waveforms include frequencies that are integer linear combinations of the stimulus frequencies. Results of decoding SSVEPs collected from nine subjects using canonical correlation analysis (CCA) with only the frequencies and harmonics as reference, also demonstrate the potential of using such a stimulation paradigm in SSVEP-based BCIs.
翻译:稳定状态的视觉发现潜力(SSVEP)是大脑-计算机界面(BCIS)中最广泛使用的模式之一,因为它有许多优点。然而,由于SSVEP中存在调音器和反应频率范围有限,因此难以在不牺牲接口其他方面或对系统施加额外限制的情况下进一步扩大目标数量。本文为SSVEP引入了一种新的多频率刺激方法,并调查其有效、高效地增加目标数量的潜力。通过在不同频率上超置刺激信号获得的拟议刺激方法,是大小效率高的,允许单步目标识别,对可用频率范围不设严格的限制,可以适合自定速度的BCIS,也不需要具体的光源。除了刺激频率及其调频外,调出的SSVEP波形还包括刺激频率的整线性组合。从九个主题中收集的SVEPs解码结果,仅以频率和调音频为参照基准,还展示了使用这种刺激范式BVEVE的可能性。