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

4 Citations (Scopus)

Abstract

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
Volume56
Issue number11
DOIs
Publication statusPublished - 2020 May 28

Bibliographical note

Funding Information:
This Letter was supported by the Industrial Core Technology Development Program through the Ministry and Trade Industry and Energy (no. 10045164) and the National Research Council of Science & Technology (NST) grant funded by the Korea government (MSIT) (no. CAP-18-01-KIST).

Funding Information:
Acknowledgments: This Letter was supported by the Industrial Core Technology Development Program through the Ministry and Trade Industry and Energy (no. 10045164) and the National Research Council of Science & Technology (NST) grant funded by the Korea government (MSIT) (no. CAP-18-01-KIST).

Publisher Copyright:
© The Institution of Engineering and Technology 2020.

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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