Use of electromyography to optimize Lokomat®settings for subject-specific gait rehabilitation in post-stroke hemiparetic patients: A proof-of-concept study.
OBJECTIVE
While generic protocols exist for gait rehabilitation using robotic orthotics such as the Lokomat®, several settings - guidance, body-weight support (BWS) and velocity - may be adjusted to individualize patient training. However, no systematic approach has yet emerged. Our objective was to assess the feasibility and effects of a systematic approach based on electromyography to determine subject-specific settings with application to the strengthening of the gluteus maximus muscle in post-stroke hemiparetic patients.


METHODS
Two male patients (61 and 65 years) with post-stroke hemiparesis performed up to 9 Lokomat®trials by changing guidance and BWS while electromyography of the gluteus maximus was measured. For each subject, the settings that maximized gluteus maximus activity were used in 20 sessions of Lokomat®training. Modified Functional Ambulation Classification (mFAC), 6-minutes walking test (6-MWT), and extensor strength were measured before and after training.


RESULTS
The greatest gluteus maximus activity was observed at (Guidance: 70% -BWS: 20%) for Patient 1 and (Guidance: 80% - BWS: 30%) for Patient 2. In both patients, mFAC score increased from 4 to 7. The additional distance in 6-MWT increased beyond minimal clinically important difference (MCID=34.4m) reported for post-stroke patients. The isometric strength of hip extensors increased by 43 and 114%.


CONCLUSIONS
Defining subject-specific settings for a Lokomat®training was feasible and simple to implement. These two case reports suggest a benefit of this approach for muscle strengthening. It remains to demonstrate the superiority of such an approach for a wider population, compared to the use of a generic protocol.
Laboratoire de simulation et modélisation du mouvement, département de kinésiologie, université de Montréal, 1700, rue Jacques-Tétreault, H7N 0B6 Laval, Québec, Canada; Centre de recherche Marie-Enfant, CHU Sainte-Justine, 5200, rue Bélanger, H1T 1C9 Montréal, Québec, Canada. Electronic address: yosra.cherni@umontreal.ca.
Yosra
Y
Cherni
Laboratoire de simulation et modélisation du mouvement, département de kinésiologie, université de Montréal, 1700, rue Jacques-Tétreault, H7N 0B6 Laval, Québec, Canada; Centre de recherche Marie-Enfant, CHU Sainte-Justine, 5200, rue Bélanger, H1T 1C9 Montréal, Québec, Canada.
Mickael
M
Begon
Laboratoire d'analyse du mouvement et de la posture (LAMP), Centre national de rééducation fonctionnelle et de réadaptation-Rehazenter, 1, rue André-Vésale, 2674 Luxembourg, Luxembourg.
Hicham
H
Chababe
Laboratoire d'analyse du mouvement et de la posture (LAMP), Centre national de rééducation fonctionnelle et de réadaptation-Rehazenter, 1, rue André-Vésale, 2674 Luxembourg, Luxembourg.
Florent
F
Moissenet
D000368:Aged; D004576:Electromyography; D020233:Gait Disorders, Neurologic / Q000150:complications / Q000503:physiopathology / Q000534:rehabilitation*; D006801:Humans; D008297:Male; D008875:Middle Aged; D018482:Muscle, Skeletal / Q000503:physiopathology; D010291:Paresis / Q000150:complications / Q000534:rehabilitation*; D057285:Precision Medicine; D012371:Robotics; D020521:Stroke / Q000150:complications*; D000071939:Stroke Rehabilitation / Q000379:methods*; D016896:Treatment Outcome
Accident vasculaire cérébral; Electromyography; Gait; Marche; Muscle strengthening; Renforcement musculaire; Robotic-assisted rehabilitation; Réadaptation assistée; Stroke; Électromyographie