Logo
    • English
    • Ελληνικά
    • Deutsch
    • français
    • italiano
    • español
  • English 
    • English
    • Ελληνικά
    • Deutsch
    • français
    • italiano
    • español
  • Login
View Item 
  •   University of Thessaly Institutional Repository
  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ.
  • View Item
  •   University of Thessaly Institutional Repository
  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ.
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.
Institutional repository
All of DSpace
  • Communities & Collections
  • By Issue Date
  • Authors
  • Titles
  • Subjects

Analyzing Dynamic Operational Conditions of Limb Prosthetic Sockets with a Mechatronics-Twin Framework

Thumbnail
Author
Chen D., Su P., Ottikkutti S., Vartholomeos P., Tahmasebi K.N., Karamousadakis M.
Date
2022
Language
en
DOI
10.3390/app12030986
Keyword
MDPI
Metadata display
Abstract
Lower limb prostheses offer a solution to restore the ambulation and self-esteem of am-putees. One key component is the prosthetic socket that serves as the interface between prosthetic device and amputee stump and thereby has a wide range of impacts on efficient fitting, appropriate load transmission, operational stability, and control. For the design and optimization of a prosthetic socket, an understanding of the actual intra-socket operational conditions becomes therefore neces-sary. This is however a difficult task due to the inherent complexity and restricted observability of socket operation. In this study, an innovative mechatronics-twin framework that integrates advanced biomechanical models and simulations with physical prototyping and dynamic operation testing for effective exploration of operational behaviors of prosthetic sockets with amputees is proposed. Within this framework, a specific Stewart manipulator is developed to enable dynamic operation testing, in particular for a well-managed generation of dynamic intra-socket loads and behaviors that are otherwise difficult to observe or realize with the real amputees. A combination of deep learning and Bayesian Inference algorithms is then employed for analyzing the intra-socket load conditions and revealing possible anomalous. © 2022 by the authorsLicensee MDPI, Basel, Switzerland.
URI
http://hdl.handle.net/11615/72777
Collections
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ. [19735]
htmlmap 

 

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

LoginRegister (MyDspace)
Help Contact
DepositionAboutHelpContact Us
Choose LanguageAll of DSpace
EnglishΕλληνικά
htmlmap