Detection of high frequency steady state visual evoked potentials for Brain-computer interfaces

Detection of high frequency steady state visual evoked potentials for Brain-computer interfaces
复制标题

DOI:
--
复制
发表时间:
2009-08
期刊:
2009 17th European Signal Processing Conference
影响因子:
--
通讯作者:
G. G. Molina-G.;D. Ibáñez;V. Mihajlović;Dmitri Chestakov
G. G. Molina-G.;D. Ibáñez;V. Mihajlović;Dmitri Chestakov
中科院分区:
其他
文献类型:
--
作者:
G. G. Molina-G.;D. Ibáñez;V. Mihajlović;Dmitri Chestakov

文献摘要

被引文献

相似文献

基于稳态视觉诱发电位(SSVEP)的脑-机接口(BCI)提供了更高的信息吞吐量,需要比其他BCI模式更短的校准周期。SSVEP是由振荡视觉刺激(例如,使用闪烁的LED)引起的振荡响应,其可以在脑电图(EEG)中检测到。SSVEP在枕叶部位更为突出,由与刺激和/或其谐波相匹配的振荡分量组成。用于最佳SSVEP检测的电极位置随着刺激的频率而改变。这里的重点是高频刺激(>30 Hz)引起的SSVEP,因为它们是最小可感知的,并防止与光诱导癫痫发作相关的安全危害。EEG信号的线性组合(空间滤波器)被用于构造表现出大的SSVEP分量的信号。与大多数依赖生物信号的应用一样,需要考虑个体特异性。因此,空间滤波器需要通过(优选地短的)校准过程针对每个BCI用户定制。在这项研究中,我们提出了一种方法来自动获得最佳的空间滤波器检测SSVEP在给定的刺激频率。我们对六名受试者的实验导致检测率,其特征在于,对于30-45 Hz范围内的刺激频率,ROC下的面积的值范围为0.8至1。
Brain-computer interfaces (BCI) based on steady-state-visual-evoked-potentials (SSVEP) offer higher information throughput and require shorter calibration periods than other BCI modalities. SSVEPs are oscillatory responses elicited by oscillatory visual stimuli (e.g. using flickering LEDs) that can be detected in the electroencephalogram (EEG). The SSVEP is more prominent in occipital sites and consists of oscillatory components matching that of the stimulus and/or its harmonics. The electrode sites for optimal SSVEP detection change with the frequency of the stimulus. The emphasis here is on SSVEPs elicited by high-frequency stimuli (>30 Hz) because they are minimally perceptible and prevent safety hazards linked to photo-induced epileptic seizures. Linear combinations of EEG signals (spatial filters) are used to construct signals exhibiting large SSVEP components. As in most applications relying on biosignals, individual specificity needs to be taken into account. Thus, the spatial filters need to be customized for each BCI user through a (preferably short) calibration procedure. In this study, we present an approach to automatically obtain the optimum spatial filters to detect the SSVEP at a given stimulation frequency. Our experiments on six subjects resulted on detection rates characterized by values of the area-under-the-ROC ranging from 0.8 to 1 for stimulation frequencies in the 30-45 Hz range.