4659993
doi
10.1109/BioRob49111.2020.9224365
oai:zenodo.org:4659993
user-h2020-sophia
user-eu
Wolfgang F. Rampeltshammer
University of Twente
Herman van der Kooij
University of Twente
Massimo Sartori
University of Twente
Myoelectric model-based control of a bi-lateral robotic ankle exoskeleton during even ground locomotion
Guillaume Durandau
University of Twente
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Myoelectric
exoskeleton
lower-limb
gait
neuromusculoskeletal model
neuromechanic model
<p>Individuals with neuromuscular injuries may fully benefit from wearable robots if a new class of wearable technologies is devised to assist complex movements seamlessly in everyday tasks. Among the most important tasks are locomotion activities. Current human-machine interfaces (HMI) are challenged in enabling assistance across wide ranges of locomoting tasks. Electromyography (EMG) and computational modelling can be used to establish an interface with the neuromuscular system. We propose an HMI based on EMG-driven musculoskeletal modelling that estimates biological joint torques in real-time and uses a percentage of these to dynamically control exoskeleton-generated torques in a task-independent manner, i.e. no need to classify locomotion modes. Proof of principle results on one subject showed that this approach could reduce EMGs during exoskeleton-assisted even ground locomotion compared to transparent mode (i.e. zero impedance). Importantly, results showed that a substantial portion of the biological ankle joint torque needed to walk was transferred from the human to the exoskeleton. That is, while the total human-exoskeleton ankle joint was always similar between assisted and zero-impedance modes, the ratio between exoskeleton-generated and human-generated torque varied substantially, with human-generated torques being dynamically compensated by the exoskeleton during assisted mode. This is a first step towards natural, continuous assistance in a large variety of movements.</p>
Zenodo
2020-10-15
info:eu-repo/semantics/conferencePaper
4659992
user-h2020-sophia
user-eu
award_title=Modelling the neuromusculoskeletal system across spatiotemporal scales for a new paradigm of human-machine motor interaction; award_number=803035; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/803035; funder_id=00k4n6c32; funder_name=European Commission;
award_title=Socio-physical Interaction Skills for Cooperative Human-Robot Systems in Agile Production; award_number=871237; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/871237; funder_id=00k4n6c32; funder_name=European Commission;
1617694092.394369
308143
md5:a5ebf392ea5ff4a3c8bfe6a837bdc112
https://zenodo.org/records/4659993/files/NMC_paper_WR2_Final.pdf
public