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Related Experiment Video

Updated: Mar 29, 2026

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Application of Brain-Computer Interactive Rehabilitation Training Combined With a Gait Robot: A Randomized Controlled

Chuan Hu1, Xin Wang1, Tongliang Pan1

  • 1Rehabilitation Treatment Center, Shandong Third Hospital, Jinan, Shandong, China.

Archives of Physical Medicine and Rehabilitation
|March 27, 2026
PubMed
Summary

Combining brain-computer interface (BCI) and gait robot (GR) training significantly improves lower-limb function and gait recovery in stroke patients. This combined approach accelerates early functional recovery more effectively than individual therapies.

Keywords:
Ambulation functionBrain–computer interactionHemiplegiaLower-limb robot trainingRehabilitationStroke

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Area of Science:

  • Neuroscience
  • Rehabilitation Medicine
  • Biomedical Engineering

Background:

  • Stroke frequently causes hemiplegia, impacting motor function and gait.
  • Traditional rehabilitation methods have limitations in restoring lost motor function.
  • Novel therapeutic approaches are needed to enhance gait recovery in post-stroke patients.

Purpose of the Study:

  • To investigate the efficacy of combining brain-computer interface (BCI) rehabilitation training with gait robot (GR) therapy for improving gait in hemiplegic stroke survivors.
  • To compare the effects of BCI, GR, and combined BCI-GR training against conventional rehabilitation.

Main Methods:

  • A randomized controlled trial involving 120 stroke patients with hemiplegia.
  • Participants were divided into four groups: control (routine training), BCI, GR, and BCI-GR.
  • Training interventions were administered daily for 8 weeks, with assessments at baseline, 4, and 8 weeks using measures like FMA-LE, BBS, FAC, IEMG, and stride parameters.

Main Results:

  • All intervention groups showed significant improvements in lower-limb function, muscle activity, and gait compared to the control group (P<.01).
  • The combined BCI-GR group demonstrated the most significant improvements in Fugl-Meyer Assessment-Lower Extremity (FMA-LE) scores (+12.93) and Berg Balance Scale (BBS) scores (+14.53).
  • BCI-GR training led to greater increases in muscle activation (IEMG) and more favorable stride parameter changes, including step frequency and step width reduction, compared to single interventions (P<.05).

Conclusions:

  • Both BCI and GR interventions are effective in improving motor function, muscle activation, and gait in post-stroke patients.
  • Combined BCI-GR training offers a synergistic effect, accelerating early functional recovery and enhancing muscle activation patterns more effectively than individual therapies.
  • This combined approach presents a promising strategy for optimizing rehabilitation outcomes in stroke survivors.