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Modeling and controlling a gait training system utilizing a biarticular muscle model
KTH, School of Computer Science and Communication (CSC), Numerical Analysis and Computer Science, NADA.
KTH, School of Computer Science and Communication (CSC), Numerical Analysis and Computer Science, NADA.ORCID iD: 0000-0003-0281-9450
KTH, School of Computer Science and Communication (CSC), Numerical Analysis and Computer Science, NADA.ORCID iD: 0000-0002-2792-1622
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2006 (English)In: Japan Society of Mechanical Engineers Symposium on Welfare Engineering, Vol. 2006, p. 234-235Article in journal (Refereed) Published
Abstract [en]

In the purpose of rehabilitation for people unable to perform a normal gait pattern a pneumatically operated gait training system with a biarticular muscle model utilizing rubbertuators have been developed. The pneumatics and the biarticular characteristics make the system difficult to control. In this research paper machine learning techniques have been used in an attempt to design a control system for the pneumatic gait. Preliminary results indicate that inverse plant modeling using Artificial Neural Networks (ANN) might be a successful approach.

Place, publisher, year, edition, pages
2006. Vol. 2006, p. 234-235
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-59781OAI: oai:DiVA.org:kth-59781DiVA, id: diva2:476308
Conference
Japan Society of Mechanical Engineers Symposium on Welfare Engineering
Note
QC 20120113Available from: 2012-01-11 Created: 2012-01-11 Last updated: 2018-01-12Bibliographically approved

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Fransen, ErikEkeberg, Örjan

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