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23: YAMAGUTIseisei 2019/04/24(水)09:59 ID:5ZbN1Z79Q(22/32) BE AAS
A.
Result I:
Predictive Model for SSVEP Magnitude Variation The purpose of this study is to select the most appropriate model to predict SSVEP magnitude variation.
Six predictive models are compared here; Poly poly2, Poly poly3, RF poly2, RF poly3, NN(GRUs) poly2 and NN(GRUs) poly3.
As shown in Table I, the mean of MSE from all predictive models is not significantly different.
However, there is a statistical difference in the mean comparison of the computational-time prediction.
One-way repeated measures ANOVA with the Greenhouse-Geisser correction reported F(1.377, 12.395) = 383.877, p<0.01.
Moreover, the Bonferroni correction and pairwise comparison presented the computational-time prediction for both textitRF poly2 and RF poly3 models as significantly lower than the other models, p<0.01.
However, RF poly2 was selected for the rest of the study since it has less complexity in polynomial degrees.
In order to obtain qualitative results, the predicted signals were plotted per time step for each experiment condition as shown in Figure 5.
B.
Result II:
Brain-Controlled Robotic Simulator
1)
Trade-off between processing window length and smooth movement: Window length plays an important role in online brain-controlled applications.
The mean of the average speed and the mean of the box deviation for varying window lengths from one to five seconds are compared in this subsection.
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AUTHOR et al.: PREPARATION OF PAPERS FOR IEEE TRANSACTIONS AND JOURNALS (FEBRUARY 2017)
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