Abstract
Our previous study established an asynchronous BCI system by using the oddball paradigm to simultaneously induce event-related potentials (ERPs) and visual evoked potentials (VEPs) (E-V BCIs). We found that stimulus onset asynchrony (SOA) is an important factor for performance since it significantly affects the ERP and VEP. Increasing the SOA increases the ERP, which improves the accuracy of detecting target stimuli. However, a larger SOA leads to a lower VEP frequency, which causes the VEP to have poor accuracy when discriminating between the brain states. How to balance the two potentials and accuracies is a problem. This study established eight SOAs from 100 ms to 375 ms that were composed of different interstimulus intervals and the same stimulus duration of 80 ms. We used a probability-based Fisher linear discriminant analysis (P-FLDA) classifier to calculate the classification accuracies of the ERP-based visual speller, VEP-based brain state discrimination, and E-V BCI. The results show that as the SOA increases, the amplitudes of N200 and P300 increase, and the accuracy also shows an increasing trend. However, the frequency of the VEP and the accuracies of state discrimination show downward trends. The change in accuracies of the E-V BCI system combining these two parts is nonlinear, and the SOA optimal value is 125 ms. The SOA of 125 ms yields the best accuracies of 95.83% and practical bit rate of 57.17 bits/min in the E-V BCI system, which provides a guideline for selecting the SOA to improve the performance.
Highlights
Brain-computer interface (BCI) is a technology that decodes brain signals to control instructions to an external device between a human and a computer [1]–[4]
In our proposed BCI system combined with Event-related potentials (ERPs) and visual evoked potentials (VEPs) (E-V BCI), we found that the setting of the stimulus onset asynchrony (SOA) was very important since it could influence the shape of the ERP and VEP
This study sets eight stimulus intervals to study the effect of the SOAs on the asynchronous ERP and VEP-based BCI
Summary
Brain-computer interface (BCI) is a technology that decodes brain signals to control instructions to an external device between a human and a computer [1]–[4]. Event-related potentials (ERPs), e.g., the N200 and P300 potentials, are brain potentials representing the peak of the cerebral cortex in the fixed latency period after the occurrence of low-probability events [8]. Visual evoked potentials include steady-state visual evoked potentials (SSVEPs) and transient visual evoked potentials (TSVEPs). SSVEP and TSVEP refer to the potentials corresponding to the stimulation frequencies. After human vision is stimulated by more than 6 Hz and less than 6 Hz, respectively [9]. The ERP and VEP are widely used in BCI, such as for wheelchair control [10] and rehabilitation [11]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
