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 language | English |
---|---|
Pages (from-to) | 528-531 |
Number of pages | 4 |
Journal | Electronics Letters |
Volume | 56 |
Issue number | 11 |
DOIs | |
Publication status | Published - 2020 May 28 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering