| Summary: | Steady-state visual evoked potentials-based brain-computer interfaces (SSVEP-BCI) can map visual stimuli with dif-ferent frequencies to certain commands to control external devices.In order to explore the capacitability of AR-BCI on the number of stimuli and the influence of the number of multi-target stimuli on the classification accuracy of AR-BCI,4 layouts of stimuli with different numbers are designed in this study and displayed through HoloLens (AR) glasses.The comparative analysis shows that the classification accuracy of the 4 layouts gradually decreases with the increase of the number of stimuli,and the location of stimuli affects the accuracy of stimulus classification.In the similar experimental paradigm,the classification results of PC screen and AR display terminals are compared,and it is found that the increasing number of stimuli has a great impact on the classification performance of AR-BCI.Current study indicates that the amount of stimulus is a key factor affecting the construction of AR-BCI in AR environment.
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