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Current Perspectives on the Biomechanical Modelling of the Human Lower Limb: A Systematic Review

Authors :
Mariana Silva
Paulo Flores
Renato Andrade
Óscar Carvalho
Bruno Freitas
João Espregueira-Mendes
Daniel Renjewski
Lehrstuhl f. Angewandte Mechanik
Source :
Archives of Computational Methods in Engineering. 28:601-636
Publication Year :
2020
Publisher :
Springer Science and Business Media LLC, 2020.

Abstract

The purpose of this systematic review is to report the characteristics and methods utilized in human lower limb or knee joint only biomechanical models to provide state-of-the-art knowledge on the topic. This review was conducted according to the preferred reporting items for systematic reviews and meta-analyses guidelines. PubMed, Scopus and Web of Science were searched up to 24th April 2018 to look for musculoskeletal models of the human lower limb or knee joint only without any associated pathology. A 15-item checklist was used to assess the methodological quality of the included studies. Twenty-one studies were included, with seventeen of them modelling the lower limb and four only the knee joint. The methodological quality of the studies varied considerably, with the reporting of model characteristics showing very low quality. Among studies including experimental setup, subjects were instructed to perform vertical jumping, running at different speeds, drop landing and isokinetic knee extension (5%), static conditions (9%), knee’s flexion/extension (14%) and walking at constant (29%) and different (33%) speeds. A great variety of modelling strategies was found for the reproduction of the human musculoskeletal system in terms of number of segments, muscles and muscle models. The reviewed musculoskeletal models were able to reproduce human movement dynamics similar to results present in literature and to experimentally measured records. However, standardized methods for reporting the characteristics and methods of these models are missing and should be addressed in future studies.

Details

ISSN :
18861784 and 11343060
Volume :
28
Database :
OpenAIRE
Journal :
Archives of Computational Methods in Engineering
Accession number :
edsair.doi.dedup.....76ac6a83051a3428a9bec591cd650e1a