Model-based control for exoskeletons with series elastic actuators evaluated on sit-to-stand movements.
Assistive robots
Exoskeleton
Model-based control
Muscle weakness
Paraplegia
Series elastic actuator
Sit-to-stand
Journal
Journal of neuroengineering and rehabilitation
ISSN: 1743-0003
Titre abrégé: J Neuroeng Rehabil
Pays: England
ID NLM: 101232233
Informations de publication
Date de publication:
03 06 2019
03 06 2019
Historique:
received:
24
01
2018
accepted:
29
04
2019
entrez:
5
6
2019
pubmed:
5
6
2019
medline:
12
2
2020
Statut:
epublish
Résumé
Currently, control of exoskeletons in rehabilitation focuses on imposing desired trajectories to promote relearning of motions. Furthermore, assistance is often provided by imposing these desired trajectories using impedance controllers. However, lower-limb exoskeletons are also a promising solution for mobility problems of individuals in daily life. To develop an assistive exoskeleton which allows the user to be autonomous, i.e. in control of his motions, remains a challenge. This paper presents a model-based control method to tackle this challenge. The model-based control method utilizes a dynamic model of the exoskeleton to compensate for its own dynamics. After this compensation of the exoskeleton dynamics, the exoskeleton can provide a desired assistance to the user. While dynamic models of exoskeletons used in the literature focus on gravity compensation only, the need for modelling and monitoring of the ground contact impedes their widespread use. The control strategy proposed here relies on modelling of the full exoskeleton dynamics and of the contacts with the environment. A modelling strategy and general control scheme are introduced. Validation of the control method on 15 non-disabled adults performing sit-to-stand motions shows that muscle effort and joint torques are similar in the conditions with dynamically compensated exoskeleton and without exoskeleton. The condition with exoskeleton in which the compensating controller was not active showed a significant increase in human joint torques and muscle effort at the knee and hip. Motor saturation occurred during the assisted condition, which limited the assistance the exoskeleton could deliver. This work presents the modelling steps and controller design to compensate the exoskeleton dynamics. The validation seems to indicate that the presented model-based controller is able to compensate the exoskeleton.
Sections du résumé
BACKGROUND
Currently, control of exoskeletons in rehabilitation focuses on imposing desired trajectories to promote relearning of motions. Furthermore, assistance is often provided by imposing these desired trajectories using impedance controllers. However, lower-limb exoskeletons are also a promising solution for mobility problems of individuals in daily life. To develop an assistive exoskeleton which allows the user to be autonomous, i.e. in control of his motions, remains a challenge. This paper presents a model-based control method to tackle this challenge.
METHODS
The model-based control method utilizes a dynamic model of the exoskeleton to compensate for its own dynamics. After this compensation of the exoskeleton dynamics, the exoskeleton can provide a desired assistance to the user. While dynamic models of exoskeletons used in the literature focus on gravity compensation only, the need for modelling and monitoring of the ground contact impedes their widespread use. The control strategy proposed here relies on modelling of the full exoskeleton dynamics and of the contacts with the environment. A modelling strategy and general control scheme are introduced.
RESULTS
Validation of the control method on 15 non-disabled adults performing sit-to-stand motions shows that muscle effort and joint torques are similar in the conditions with dynamically compensated exoskeleton and without exoskeleton. The condition with exoskeleton in which the compensating controller was not active showed a significant increase in human joint torques and muscle effort at the knee and hip. Motor saturation occurred during the assisted condition, which limited the assistance the exoskeleton could deliver.
CONCLUSIONS
This work presents the modelling steps and controller design to compensate the exoskeleton dynamics. The validation seems to indicate that the presented model-based controller is able to compensate the exoskeleton.
Identifiants
pubmed: 31159874
doi: 10.1186/s12984-019-0526-8
pii: 10.1186/s12984-019-0526-8
pmc: PMC6547546
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
65Subventions
Organisme : Agentschap voor Innovatie door Wetenschap en Technologie
ID : IWT-SBO 131381
Pays : International
Organisme : Agentschap voor Innovatie door Wetenschap en Technologie (BE)
ID : IWT-SBO
Pays : International
Organisme : Agentschap voor Innovatie door Wetenschap en Technologie (BE)
ID : MIRAD, IWT-SBO 120057
Pays : International
Organisme : Fonds Wetenschappelijk Onderzoek
ID : 11Z1815N
Pays : International
Références
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:462-6
pubmed: 21095652
IEEE Trans Neural Syst Rehabil Eng. 2004 Mar;12(1):24-31
pubmed: 15068184
J Electromyogr Kinesiol. 2000 Oct;10(5):361-74
pubmed: 11018445
IEEE Trans Neural Syst Rehabil Eng. 2017 Feb;25(2):171-182
pubmed: 26829794
IEEE Trans Neural Syst Rehabil Eng. 2015 Mar;23(2):277-86
pubmed: 25373109
Nature. 2015 Jun 11;522(7555):212-5
pubmed: 25830889
J Biomech. 2013 Sep 27;46(14):2394-401
pubmed: 23948374
Med Eng Phys. 2012 May;34(4):397-408
pubmed: 22177895
IEEE Trans Neural Syst Rehabil Eng. 2010 Feb;18(1):38-48
pubmed: 20194054
Clin Biomech (Bristol, Avon). 1994 Jul;9(4):235-44
pubmed: 23916233
IEEE Trans Biomed Eng. 2013 Jul;60(7):1912-9
pubmed: 23380850
Science. 2017 Jun 23;356(6344):1280-1284
pubmed: 28642437
Sci Robot. 2017 Jan 18;2(2):
pubmed: 33157865
IEEE Trans Biomed Eng. 2007 Nov;54(11):1940-50
pubmed: 18018689
Biomed Eng Online. 2014 Aug 04;13:111
pubmed: 25092209
J Neuroeng Rehabil. 2015 Jan 05;12:1
pubmed: 25557982