Deep learning models for stable gait prediction applied to exoskeleton reference trajectories for children with cerebral palsy

HIGHLIGHTS

• who: Cerebral, Palsy and KONSTANTINOS, SIRLANTZIS from the School of Engineering, University of Kent, Canterbury , NT, UK have published the research work: Deep Learning Models for Stable Gait Prediction Applied to Exoskeleton Reference Trajectories for Children with Cerebral Palsy, in the Journal: (JOURNAL)
• what: The authors implement four deep learning models (LSTM FCN CNN and Transformer) that perform one-step-ahead gait trajectory prediction after training on gait patterns of typically developing children. The authors propose a methodology that optimises for stability in long-term forecasts and evaluate the performance of the models on typically . . .
  

   

  

  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.