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Mining EEG scalp maps of independent components related to HCT tasks
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Resumo(s)
This work presents an unsupervised mining strat-
egy, applied to an independent component analysis (ICA) of
segments of data collected while participants are answering
to the items of the Halstead Category Test (HCT). This new
methodology was developed to achieve signal components at
trial level and therefore to study signal dynamics which are
not available within participants’ ensemble average signals.
The study will be focused on the signal component that can
be elicited by the binary visual feedback which is part of the
HCT protocol. The experimental study is conducted using a
cohort of 58 participants.
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IEEE