Multimodal human-exoskeleton interface for lower limb movement prediction through a dense co-attention symmetric mechanism

HIGHLIGHTS

• who: Rui Huang from the School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China, School of have published the article: Multimodal Human-Exoskeleton Interface for Lower Limb Movement Prediction Through a Dense Co-Attention Symmetric Mechanism, in the Journal: (JOURNAL)
• what: The aim of this article is to design a human-exoskeleton interface for hemiplegic lower limb rehabilitation training. In terms of movement prediction models based on traditional machine_learning, the authors compare the performance of DMEFNet with six traditional movement prediction models based on handcrafted features. In Section 4.3 . . .
  

   

  

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