Identifying the different neural strategies that a person may adopt to perform simple locomotor tasks, such as walking, may enable the definition of rehabilitation plans aimed to reduce joint loads while preserving joint kinematics. Abnormal detrimental loading conditions that would likely reduce a person’s quality of life, especially among the elderly, could thus be prevented. Leveraging on previous works, we employed musculoskeletal models and biomechanical simulations (1) to explore how healthy young and elder adults recruit their muscles to perform a walking task, and (2) to determine whether the use of electromyography data to inform the simulations would allow to reduce the solution space. For the 15 tested subjects (10 young, 5 elderly), we estimated 10k sets of muscle and knee joint contact forces combining a static optimization approach with a Markov-chain Monte Carlo algorithm. We observed that the bands of solutions were narrower among the young adults than the elderly, showing how different neural strategies that prioritize the use of different muscles while ensuring the same kinematics are more likely to result in larger changes in the joint contact forces among older adults. In addition, while the neural strategies associated to the maximal knee contact forces were similar between populations, some differences emerged when analysing the strategies to minimise the knee loads. Last, the use of electromyography data allowed for a reduction of the solution band by up to 69%.

Davico, G., Toccaceli, E., Labanca, L., Benedetti, M.G., Viceconti, M. (2026). Exploring the effect of different neural strategies on the knee joint contact forces during walking in adults. SCIENTIFIC REPORTS, 16(1), 1-15 [10.1038/s41598-026-46419-8].

Exploring the effect of different neural strategies on the knee joint contact forces during walking in adults

Davico, Giorgio
Primo
;
Toccaceli, Enrico;Benedetti, Maria Grazia;Viceconti, Marco
2026

Abstract

Identifying the different neural strategies that a person may adopt to perform simple locomotor tasks, such as walking, may enable the definition of rehabilitation plans aimed to reduce joint loads while preserving joint kinematics. Abnormal detrimental loading conditions that would likely reduce a person’s quality of life, especially among the elderly, could thus be prevented. Leveraging on previous works, we employed musculoskeletal models and biomechanical simulations (1) to explore how healthy young and elder adults recruit their muscles to perform a walking task, and (2) to determine whether the use of electromyography data to inform the simulations would allow to reduce the solution space. For the 15 tested subjects (10 young, 5 elderly), we estimated 10k sets of muscle and knee joint contact forces combining a static optimization approach with a Markov-chain Monte Carlo algorithm. We observed that the bands of solutions were narrower among the young adults than the elderly, showing how different neural strategies that prioritize the use of different muscles while ensuring the same kinematics are more likely to result in larger changes in the joint contact forces among older adults. In addition, while the neural strategies associated to the maximal knee contact forces were similar between populations, some differences emerged when analysing the strategies to minimise the knee loads. Last, the use of electromyography data allowed for a reduction of the solution band by up to 69%.
2026
Davico, G., Toccaceli, E., Labanca, L., Benedetti, M.G., Viceconti, M. (2026). Exploring the effect of different neural strategies on the knee joint contact forces during walking in adults. SCIENTIFIC REPORTS, 16(1), 1-15 [10.1038/s41598-026-46419-8].
Davico, Giorgio; Toccaceli, Enrico; Labanca, Luciana; Benedetti, Maria Grazia; Viceconti, Marco
File in questo prodotto:
File Dimensione Formato  
unpaywall-bitstream-846318795.pdf

accesso aperto

Tipo: Versione (PDF) editoriale / Version Of Record
Licenza: Creative commons
Dimensione 2.21 MB
Formato Adobe PDF
2.21 MB Adobe PDF Visualizza/Apri
41598_2026_46419_MOESM1_ESM.docx

accesso aperto

Tipo: File Supplementare
Licenza: Licenza per Accesso Aperto. Creative Commons Attribuzione (CCBY)
Dimensione 527.94 kB
Formato Microsoft Word XML
527.94 kB Microsoft Word XML Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1065970
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
  • OpenAlex ND
social impact