Individualized Training of Back Muscles Using Iterative Learning Control of a Compliant Balance Board

Elisabeth Jensen, Reihaneh Mirjalili, Kim Peper, Dennis Ossadnik, Fan Wu, Jan Lang, Matthias Martin, Florian Hetfleisch, Rainer Burgkart, Sami Haddadin

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

Abstract

Here we present the GyroTrainer, a bespoke mechatronic balance board system designed to trigger activation of the back muscles while the user engages in a balance-challenging game. The GyroTrainer uses admittance control coupled with an iterative learning approach so as to tailor the admittance control parameters, i.e. difficulty level, according to the user's skill. Our experimental evaluation demonstrated that an individualized admittance control stiffness could be identified for each user, which corresponds with a desired level of difficulty and increased back muscle activity. A first game implementation demonstrates the feasibility of utilizing the GyroTrainer system and the individually identified admittance control stiffness for gamification of back muscle training.

OriginalspracheEnglisch
Titel2023 International Conference on Rehabilitation Robotics, ICORR 2023
Herausgeber (Verlag)IEEE Computer Society
ISBN (elektronisch)9798350342758
DOIs
PublikationsstatusVeröffentlicht - 2023
Veranstaltung2023 International Conference on Rehabilitation Robotics, ICORR 2023 - Singapore, Singapur
Dauer: 24 Sept. 202328 Sept. 2023

Publikationsreihe

NameIEEE International Conference on Rehabilitation Robotics
ISSN (Print)1945-7898
ISSN (elektronisch)1945-7901

Konferenz

Konferenz2023 International Conference on Rehabilitation Robotics, ICORR 2023
Land/GebietSingapur
OrtSingapore
Zeitraum24/09/2328/09/23

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