Deep learning-based BCI for gait decoding from EEG with LSTM recurrent neural network

Abstract

Our results support for the first time the use of a memory-based deep learning classifier to decode walking activity from non-invasive brain recordings. We suggest that this classifier, exploited in real time, can be a more effective input for devices restoring locomotion in impaired people.