An EMG-assisted muscle-force driven finite element analysis pipeline to investigate joint- and tissue-level mechanical responses in functional activities: towards a rapid assessment toolbox
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Stenroth, L
Mononen, ME
Vartiainen, PEJ
Tanska, P
Karjalainen, PA
Suomalainen, JS
Arokoski, JPA
Saxby, D
Lloyd, DG
Korhonen, RK
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Abstract
Joint tissue mechanics (e.g., stress and strain) are believed to have a major involvement in the onset and progression of musculoskeletal disorders, e.g., knee osteoarthritis (KOA). Accordingly, considerable efforts have been made to develop musculoskeletal finite element (MS-FE) models to estimate highly detailed tissue mechanics that predict cartilage degeneration. However, creating such models is time-consuming and requires advanced expertise. This limits these complex, yet promising MS-FE models to research applications with few participants and makes the models impractical for clinical assessments. Also, these previously developed MS-FE models have not been used to assess activities other than gait. This study introduces and verifies a semi-automated rapid state-of-the-art MS-FE modeling and simulation toolbox incorporating an electromyography- (EMG) assisted MS model and a muscle-force driven FE model of the knee with fibril-reinforced poro(visco)elastic cartilages and menisci. To showcase the usability of the pipeline, we estimated joint- and tissue-level knee mechanics in 15 KOA individuals performing different daily activities. The pipeline was verified by comparing the estimated muscle activations and joint mechanics to existing experimental data. To determine the importance of EMG-assisted MS approach, results were compared to those from the same FE models but driven by static-optimization-based MS models. The EMG-assisted MS-FE pipeline bore a closer resemblance to experiments compared to the static-optimization-based MS-FE pipeline. Importantly, the developed pipeline showed great potential as a rapid MS-FE analysis toolbox to investigate multiscale knee mechanics during different activities of individuals with KOA. The template FE model of the study is freely available here.
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IEEE Transactions on Biomedical Engineering
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© The Authors 2022. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
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Artificial intelligence
Biomedical engineering
Electronics, sensors and digital hardware
Computer vision and multimedia computation
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Esrafilian, A; Stenroth, L; Mononen, ME; Vartiainen, PEJ; Tanska, P; Karjalainen, PA; Suomalainen, JS; Arokoski, JPA; Saxby, D; Lloyd, DG; Korhonen, RK, An EMG-assisted muscle-force driven finite element analysis pipeline to investigate joint- and tissue-level mechanical responses in functional activities: towards a rapid assessment toolbox, IEEE Transactions on Biomedical Engineering, 2022