A novel stimulation for multi-class SSVEP-based brain-computer interface using patterns of time-varying frequencies

Abstract

Steady-state visual evoked potential (SSVEP) has become one of the most widely employed modalities in online brain computer interface (BCI) because of its high signal-to-noise ratio. However, due to the limitations of brain physiology and the refresh rate of the display devices, the available stimulation frequencies that evoke strong SSVEPs are generally limited for practical applications. In this paper, we introduce a novel stimulation method using patterns of time-varying frequencies that can increase the number of visual stimuli with a fixed number of stimulation frequencies for use in multi-class SSVEP-based BCI systems. We then propose a probabilistic framework and investigate three approaches to detect different patterns of time-varying frequencies. The results confirmed that our proposed stimulation is a promising method for multi-class SSVEP-based BCI tasks. Our pattern detection approaches improved the detection performance significantly by extracting higher quality discriminative information from the input signal.

A novel multiple time-frequency sequential coding strategy for hybrid brain-computer interface

“…Table 1 lists the number of stimuli sequences generated theoretically in the different stimuli durations and different omission numbers under the extended MTFSC protocol. Compared with previous research, a slight increase in the stimuli duration in this method largely improved the number of targets (Zhang et al, 2012;Dehzangi et al, 2014;Xu et al, 2020).…”

“…Although the features in the single frame are blurred, the coding feature formed by these features helps to identify the specific target. It was interesting to note that, visually speaking (Figure 13), these stimuli look more like the c-VEP stimuli as more f-VEP information was used in f-VEP stimuli, compared to those adopting only one periodic code or event (Mukesh et al, 2005;Zhang et al, 2012;Hwang et al, 2013;Yin et al, 2013aYin et al, , 2015Dehzangi et al, 2014). Besides, the target recognition method was also similar.…”

“…Besides, they used an extra LED device to provide stimulation frequency, which was not convenient to use on the computer. Using sequential coding methods for time-frequency paradigms has also been studied in previous research (Zhang et al, 2012;Kimura et al, 2013;Dehzangi et al, 2014). However, only frequency sequences (sequence with multi-frequency) were used in their research.…”

Portable Brain-Computer Interface for the Intensive Care Unit Patient Communication Using Subject-Dependent SSVEP Identification

“…This is significant, not only for patients with spinal cord injury and stroke, most of whom are initially admitted to an ICU, but to the potentially large number of patients in the intensive care who cannot use a picture board or other finger contact systems because of a critical Neuropathy/Myopathy illness or an acute brain injury that causes weakness. Our objective is to create an end-to-end steady-state visual evoked potential- (SSVEP-) based wireless BCI system to facilitate communication with intubated patients in the intensive care [ 28 – 30 ]. The portable BCI device of interest in this study functions through visual attention to illustrative icons displayed on an Android tablet screen.…”