Hybrid Human-Machine Interface for Gait Decoding Through Bayesian Fusion of EEG and EMG Classifiers

Hybrid Human-Machine Interface for Gait Decoding Through Bayesian Fusion of EEG and EMG Classifiers

Despite the advances in the field of brain computer interfaces (BCI), the use of the sole electroencephalography (EEG) signal to control walking rehabilitation devices is currently not viable in clinical settings, due to its unreliability. Hybrid interfaces (hHMIs) represent a very recent solution t...

Full description

Bibliographic Details
Main Authors: Stefano Tortora, Luca Tonin, Carmelo Chisari, Silvestro Micera, Emanuele Menegatti, Fiorenzo Artoni
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-11-01
Series:Frontiers in Neurorobotics
Subjects:
EEG
EMG
hybrid BCI
Bayesian inference
LSTM network
mobile brain/body imaging
Online Access:https://www.frontiersin.org/articles/10.3389/fnbot.2020.582728/full

Internet

https://www.frontiersin.org/articles/10.3389/fnbot.2020.582728/full

Similar Items