Hybrid human-machine interface for gait decoding through bayesian fusion of eeg and emg classifiers

HIGHLIGHTS

• who: Stefano Tortora from the Department of Information Engineering, University of Padova, Padova, Italy, Unit of Neurorehabilitation, Department of have published the Article: Hybrid Human-Machine Interface for Gait Decoding Through Bayesian Fusion of EEG and EMG Classifiers, in the Journal: (JOURNAL)
• what: In this study, two separated LSTM networks, running in parallel, were implemented to decode gait events from EEG and EMG, respectively, and their predictions are subsequently integrated (see section 2.4). To evaluate the performance of the proposed hybrid_approach, that integrates the information from the brain signals to support the compromised muscular . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or E-mail:

  If you don't have an account, you can create one here.