Myoelectric model-based control of a bi-lateral robotic ankle exoskeleton during even ground locomotion

Guillaume Durandau, Wolfgang F. Rampeltshammer, Herman Van Der Kooij, Massimo Sartori

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

5 Citations (Scopus)
160 Downloads (Pure)

Abstract

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.

Original languageEnglish
Title of host publication2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, BioRob 2020
PublisherIEEE
Pages822-826
Number of pages5
ISBN (Electronic)9781728159072
DOIs
Publication statusPublished - Nov 2020
Event8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, BioRob 2020 - Virtual Conference, New York City, United States
Duration: 29 Nov 20201 Dec 2020
Conference number: 8
https://biorob2020nyc.org/

Publication series

NameProceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
Volume2020-November
ISSN (Print)2155-1774

Conference

Conference8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, BioRob 2020
Abbreviated titleBioRob 2020
Country/TerritoryUnited States
CityNew York City
Period29/11/201/12/20
Internet address

Keywords

  • 22/2 OA procedure

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