Publication . Blanco-Mora, D. A.; Aldridge, A.; Jorge, C.; Vourvopoulos, A.; Figueiredo, P.; Bermúdez i Badia, S.
Motor imagery classification using electroencephalography is based on feature extraction over a length of
time, and different configurations of settings can alter the performance of a classifier. Nevertheless, there
is a lack of standardized settings for motor imagery classification. This work analyzes the effect of age on
motor imagery training performance for two common spatial pattern-based classifier pipelines and various
configurations of timing parameters, such as epochs, windows, and offsets. Results showed significant (p
≤ 0.01) inverse correlations between performance and feature quantity, as well as between performance and
epoch/window ratio.
