Toward Tailored Rehabilitation by Implementation of a Novel Musculoskeletal Finite Element Analysis Pipeline

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  • Amir Esrafilian
  • Stenroth, Lauri
  • Mika E. Mononen
  • Paavo Vartiainen
  • Petri Tanska
  • Pasi A. Karjalainen
  • Juha Sampo Suomalainen
  • Jari P.A. Arokoski
  • David J. Saxby
  • David G. Lloyd
  • Rami K. Korhonen

Tissue-level mechanics (e.g., stress and strain) are important factors governing tissue remodeling and development of knee osteoarthritis (KOA), and hence, the success of physical rehabilitation. To date, no clinically feasible analysis toolbox has been introduced and used to inform clinical decision making with subject-specific in-depth joint mechanics of different activities. Herein, we utilized a rapid state-of-the-art electromyography-assisted musculoskeletal finite element analysis toolbox with fibril-reinforced poro(visco)elastic cartilages and menisci to investigate knee mechanics in different activities. Tissue mechanical responses, believed to govern collagen damage, cell death, and fixed charge density loss of proteoglycans, were characterized within 15 patients with KOA while various daily activities and rehabilitation exercises were performed. Results showed more inter-participant variation in joint mechanics during rehabilitation exercises compared to daily activities. Accordingly, the devised workflow may be used for designing subject-specific rehabilitation protocols. Further, results showed the potential to tailor rehabilitation exercises, or assess capacity for daily activity modifications, to optimally load knee tissue, especially when mechanically-induced cartilage degeneration and adaptation are of interest.

OriginalsprogEngelsk
TidsskriftIEEE Transactions on Neural Systems and Rehabilitation Engineering
Vol/bind30
Sider (fra-til)789-802
ISSN1534-4320
DOI
StatusUdgivet - 2022

Bibliografisk note

Funding Information:
This work was supported in part by the National Health and Medical Research Council of Australia under Grant 2001734; in part by the European Union's Horizon 2020 Research and Innovation Program under theMarie Sklodowska-Curie Grant 713645; in part by the Academy of Finland under Grant 324529, Grant 324994, Grant 328920, Grant 332915, and Grant 334773 (under the frame of ERA PerMed); in part by the Sigrid Juselius Foundation; in part by the Business Finland under Grant 3455/31/2019; in part by the Finnish Cultural Foundation under Grant 191044 and Grant 200059; in part by the Päivikki and Sakari Sohlberg Foundation; in part by the Innovation Fund Denmark under Grant 9088-00006B (under the frame of ERA PerMed); in part by the European Regional Development Fund (Regional Council of Pohjois- Savo) and the University of Eastern Finland under Projects: Human measurement and analysis—research and innovation laboratories under Project A73200 and Project A73241; and in part by the Digital Technology RDI Environment under Project A74338

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