Practical method for predicting intended gait speed via soleus surface EMG signals

J. Kim, S. H. Chung, J. Choi, J. M. Lee, S. J. Kim

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


The lack of patient effort during robot-assisted gait training (RAGT) is thought to be the main factor behind unsatisfactory rehabilitative efficacy among hemiparetic stroke patients. A key milestone to implement patient-driven RAGT is to predict gait intent prior to actual joint movement. Here, the authors propose a method of predicting step speed intent via surface electromyogram (EMG) signals from the soleus. Six lower-limb muscles were initially evaluated on a treadmill, and the results suggest that the soleus EMG signals correlate well with step speed. The authors further propose a simple linear regression model which predicts subsequent step speed via current soleus EMG signals with over-ground gait sessions, R2 of ∼0.6. The proposed experimental results and simple prediction model should be applicable for RAGT without significant modifications.

Original languageEnglish
Pages (from-to)528-531
Number of pages4
JournalElectronics Letters
Issue number11
Publication statusPublished - 2020 May 28

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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