4 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 in the study consists of EEG and fNIRS recordings from 29 healthy subjects performing left and right-hand MI tasks.