Transient brain activity explains the spectral content of steady-state visual evoked potentials.
EMBC（2014）
摘要
Steady-state visual evoked potentials (SSVEPs) are widely used in the design of brain-computer interfaces (BCIs). A lot of effort has therefore been devoted to find a fast and reliable way to detect SSVEPs. We study the link between transient and steady-state VEPs and show that it is possible to predict the spectral content of a subject's SSVEPs by simulating trains of transient VEPs. This could lead to a better understanding of evoked potentials as well as to better performances of SSVEP-based BCIs, by providing a tool to improve SSVEP detection algorithms.
更多查看译文
关键词
medical signal detection,neurophysiology,electroencephalography,brain-computer interfaces,transient brain activity,medical signal processing,ssvep-based bci detection algorithms,visual evoked potentials,spectral content prediction,transient steady-state visual evoked potentials,steady-steady-state visual evoked potentials,brain-computer interface design
AI 理解论文
溯源树
样例
生成溯源树，研究论文发展脉络
Chat Paper
正在生成论文摘要