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Estimation of muscular metabolic power in two different cross-country sit-skiing sledges using inverse-dynamics simulation
Swedish Winter Sports Research Centre, Department of Health Sciences, Mid Sweden University, Östersund, Sweden.ORCID iD: 0000-0001-5317-2779
Sports Tech Research Centre, Department of Quality Management and Engineering Technology, Mid Sweden University, Östersund, Sweden.ORCID iD: 0000-0002-9205-6807
Linköping University, Department of Management and Engineering, Solid Mechanics. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-6267-3847
2022 (English)In: Journal of Rehabilitation and Assistive Technologies Engineering, ISSN 2055-6683, Vol. 9Article in journal (Refereed) Published
Abstract [en]

The aim of this study was to estimate and compare the muscular metabolic power produced in the human body using musculoskeletal inverse-dynamics during cross-country sit-skiing. Two sitting positions were adapted for athletes with reduced trunk and hip muscle control, knee low with frontal trunk support (KL-fix), and knee high (KH). Five female national class able-bodied cross-country skiers performed submaximal and maximal exercise in both sitting positions, while recording 3-D kinematics, pole forces, electromyography and respiratory variables. Simulations were performed from these experimental results and muscular metabolic power was computed. The main part of the muscle metabolic power was produced in the upper limbs for both sitting positions, but KH produced more muscle metabolic power in lower limbs and trunk during maximal intensity. KH was also more efficient, utilizing less muscular metabolic power during submaximal intensities, relatively less power in the upper limbs and more power in the trunk, hip and lower limb muscles. This implies that sitting position KH is preferable for high power output when using able-bodied simulation models. This study showed the potential of using musculoskeletal simulations to improve the understanding of how different equipment design and muscles contribute to performance.

Place, publisher, year, edition, pages
Sage Publications Inc , 2022. Vol. 9
Keywords [en]
kinematics; kinetics; musculoskeletal modeling; para sports
National Category
Applied Mechanics Sport and Fitness Sciences Other Medical Biotechnology
Identifiers
URN: urn:nbn:se:liu:diva-189155DOI: 10.1177/20556683221131557ISI: 000865795000001PubMedID: 36225652OAI: oai:DiVA.org:liu-189155DiVA, id: diva2:1702846
Note

Funding: Promobilia foundation, Sweden [14141]

Available from: 2022-10-11 Created: 2022-10-11 Last updated: 2025-02-11

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Holmberg, Joakim

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Lund Ohlsson, MarieDanvind, JonasHolmberg, Joakim
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