International Symposium on Affective Science and Engineering
Online ISSN : 2433-5428
Session ID : AM-1B-3
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Affective Robotics
Basic Research of 50-Selective Steady State Visual Evoked Potential Brain-Computer Interface
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The key parameters in the brain-computer interface (BCI) are input speed, accuracy, ease of use, and the number of inputs. Steady state visual evoked potential (SSVEP)-BCIs, which are excellent in the previous three categories, have problems with the number of inputs. We designed a 50-selective SSVEP-BCI to increase the number of inputs to realize Japanese and PC keyboard input in the future. To increase the number of inputs, we improved the frequency resolution. The number of inputs can be doubled by changing the resolution of the stimuli from 0.2 to 0.1Hz. This is because it is possible to double the number of inputs. We conducted canonical correlation analysis on the subject’s raw and pseudo-signal data. The noise is extremely large, and the conventional analysis method that outputs the maximum value of the canonical correlation vector has a low positive response rate. Thus, we ran a frequency band restriction that discriminates SSVEP components with a threshold by frequency. We also introduced a majority voting algorithm to eliminate the nontypeable data. Consequently, the average correct response rate was 55.11%, and the maximum was 79.53%; the average information transfer rate was 28.05 bits/min, and the maximum was 45.16 bits/min. Therefore, the experimental results show that the number of inputs can increase with improved frequency resolution.

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