Kim, J. Chung, S. H. Choi, J. Lee, J. M. Kim, S-J 2024-01-19T17:32:12Z 2024-01-19T17:32:12Z 2021-09-05 2020-05-28 0013-5194 https://pubs.kist.re.kr/handle/201004/118602 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, R-2 of similar to 0.6. The proposed experimental results and simple prediction model should be applicable for RAGT without significant modifications. English INST ENGINEERING TECHNOLOGY-IET TREADMILL WALKING STROKE PATIENTS Practical method for predicting intended gait speed via soleus surface EMG signals Article 10.1049/el.2020.0090 1 ELECTRONICS LETTERS, v.56, no.11, pp.528 - 530 ELECTRONICS LETTERS 56 11 528 530 scie scopus 000537284100003 2-s2.0-85085387842 Engineering, Electrical & Electronic Engineering Article TREADMILL WALKING STROKE PATIENTS medical robotics electromyography patient rehabilitation regression analysis gait analysis medical signal processing intended gait speed soleus surface EMG signals patient effort robot-assisted gait training hemiparetic stroke patients patient-driven RAGT gait intent joint movement step speed intent surface electromyogram signals lower-limb muscles simple linear regression model over-ground gait sessions rehabilitative efficacy soleus EMG signals