Author version made available in accordance with publisher copyright policy. The final publication is available at link.springer.com.EEG recording is a time consuming operation during which
the subject is expected to stay still for a long time performing tasks. It
is reasonable to expect some
uctuation in the level of focus toward the
performed task during the task period. This study is focused on investi-
gating various approaches for emphasizing regions of interest during the
task period. Dividing the task period into three segments of beginning,
middle and end, is expectable to improve the overall classi cation per-
formance by changing the concentration of the training samples toward
regions in which subject had better concentration toward the performed
tasks. This issue is investigated through the use of techniques such as
i) replication, ii) biasing, and iii) overlapping. A dataset with 4 motor
imagery tasks (BCI Competition III dataset IIIa) is used. The results il-
lustrate the existing variations within the potential of di erent segments
of the task period and the feasibility of techniques that focus the training
samples toward such regions
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