Age-Related Differences in MVEP and SSMVEP-Based BCI Performance
INTELLIGENT ROBOTICS AND APPLICATIONS (ICIRA 2022), PT II（2022）
Chongqing Univ
Abstract
With the aggravation of the aging society, the proportion of senior is gradually increasing. The brain structure size is changing with age. Thus, a certain of researchers focus on the differences in EEG responses or brain computer interface (BCI) performance among different age groups. Current study illustrated the differences in the transient response and steady state response to the motion checkerboard paradigm in younger group (age ranges from 22 to 30) and senior group (age ranges from 60 to 75) for the first time. Three algorithms were utilized to test the performance of the four-targets steady state motion visual evoked potential (SSMVEP) based BCI. Results showed that the SSMVEP could be clearly elicited in both groups. And two strong transient motion related components i.e., P1 and N2 were found in the temporal waveform. The latency of P1 in senior group was significant longer than that in younger group. And the amplitudes of P1 and N2 in senior group were significantly higher than that in younger group. For the performance of identifying SSMVEP, the accuracies in senior group were lower than that in younger group in all three data lengths. And extended canonical correlation analysis (extended CCA)-based method achieved the highest accuracy (86.39% +/- 16.37% in senior subjects and 93.96% +/- 5.68% in younger subjects) compared with CCA-based method and task-related component analysis-based method in both groups. These findings may be helpful for researchers designing algorithms to achieve high classification performance especially for senior subjects.
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Key words
Age,Brain-computer interface,Steady state motion visual evoked potential,Motion visual evoked potential,Electroencephalogram
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