Toward Multimodal Human-Robot Interaction to Enhance Active Participation of Users in Gait Rehabilitation

Kai Gui, Honghai Liu, Dingguo Zhang

Research output: Contribution to journalArticlepeer-review

73 Citations (SciVal)


Robotic exoskeletons for physical rehabilitation have been utilized for retraining patients suffering from paraplegia and enhancing motor recovery in recent years. However, users are not voluntarily involved in most systems. This paper aims to develop a locomotion trainer with multiple gait patterns, which can be controlled by the active motion intention of users. A multimodal human-robot interaction (HRI) system is established to enhance subject's active participation during gait rehabilitation, which includes cognitive HRI (cHRI) and physical HRI (pHRI). The cHRI adopts brain-computer interface based on steady-state visual evoked potential. The pHRI is realized via admittance control based on electromyography. A central pattern generator is utilized to produce rhythmic and continuous lower joint trajectories, and its state variables are regulated by cHRI and pHRI. A custom-made leg exoskeleton prototype with the proposed multimodal HRI is tested on healthy subjects and stroke patients. The results show that voluntary and active participation can be effectively involved to achieve various assistive gait patterns.

Original languageEnglish
Article number7926461
Pages (from-to)2054-2066
Number of pages13
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Issue number11
Early online date11 May 2017
Publication statusPublished - 6 Nov 2017


  • active participation
  • brain-computer interface
  • central pattern generator
  • Cognitive human-robot interaction
  • gait rehabilitation
  • physical human-robot interaction

ASJC Scopus subject areas

  • General Neuroscience
  • Biomedical Engineering
  • Computer Science Applications


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