Knee joint contact forces predicted via an EMG-assisted approach and Static Optimization vs in vivo data from an instrumented implant

Davico, Giorgio ; Princelle, Domitille (2024) Knee joint contact forces predicted via an EMG-assisted approach and Static Optimization vs in vivo data from an instrumented implant. Alma Mater Studiorum - Università di Bologna. DOI 10.6092/unibo/amsacta/7528. [Dataset]
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Abstract

This dataset contains data generated as part of a study aimed to assess the predictive accuracy of two common approaches, i.e. Static Optimization and EMG-assisted approach, to estimate knee joint contact forces during an overground walking task, using musculoskeletal models. The analyses are based on publicly available data collected as part of the last four editions of the Grand Challenge Competition to Predict In Vivo Knee Loads (Fregly et al., 2012), which can be accessed and downloaded at this link: https://simtk.org/projects/kneeloads.

Abstract
Tipologia del documento
Dataset
Autori
AutoreAffiliazioneORCID
Davico, GiorgioAlma Mater Studiorum - University of Bologna; IRCCS Istituto Ortopedico Rizzoli0000-0002-2046-529X
Princelle, DomitilleAlma Mater Studiorum - University of Bologna; IRCCS Istituto Ortopedico Rizzoli0000-0002-1215-9268
Parole chiave
Musculokseletal model, Subject-specific model, image-based model, joint load, predictive accuracy
Settori scientifico-disciplinari
DOI
Contributors
Contributor
Affiliazione
ORCID
Tipo
Davico, Giorgio
Alma Mater Studiorum - University of Bologna; IRCCS Istituto Ortopedico Rizzoli
Contact person
Princelle, Domitille
Alma Mater Studiorum - University of Bologna; IRCCS Istituto Ortopedico Rizzoli
Researcher
Viceconti, Marco
Alma Mater Studiorum - University of Bologna; IRCCS Istituto Ortopedico Rizzoli
Supervisor
Data di deposito
26 Gen 2024 08:41
Ultima modifica
29 Gen 2024 14:58
Nome del Progetto
ISW - In Silico World: Lowering barriers to ubiquitous adoption of In Silico Trials
Programma di finanziamento
EC - H2020
URI

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