6 datasets found

The proposed method uses two publicly available motor imagery EEG datasets for validation.

The dataset used in the study of FingerNet, a deep neural network for fine motor imagery classification using EEG signals.

The dataset consists of records of 52 first year students who completed the undergraduate engineering course (out of 115 registered students) at the University of Genoa.

The dataset used for EEG signal decoding, featuring motor imagery (MI) and steady-state visual evoked potential (SSVEP) tasks.

The dataset used for EEG signal decoding, featuring motor imagery (MI) and steady-state visual evoked potential (SSVEP) tasks.

The OpenBMI dataset is a large benchmark containing 2 sessions of 2-class MI-EEG data (left hand, right hand) from 54 right-handed healthy subjects.