Deep learning-based BCI for gait decoding from EEG with LSTM recurrent neural network.
Journal:
Journal of neural engineering
Published Date:
Jul 13, 2020
Abstract
OBJECTIVE: Mobile Brain/Body Imaging (MoBI) frameworks allowed the research community to find evidence of cortical involvement at walking initiation and during locomotion. However, the decoding of gait patterns from brain signals remains an open challenge. The aim of this work is to propose and validate a deep learning model to decode gait phases from Electroenchephalography (EEG).