Predictive Models in Biomechanics

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

This paper investigates the opportunity of predictive musculoskeletal models that do not require experimental input of kinematics and ground reaction forces. First, the requirements of such models are reviewed and, subsequent-ly, an example model of running is derived by means of principal component analysis. The generation of different running styles using the model is demonstrated, and we conclude that this type of models has the potential to predict motion behavior given shallow input describing the individual.
Original languageEnglish
Title of host publicationBiomechanics in Medicine and Biology : Proceedings of the International Conference of the Polish Society of Biomechanics, Zielona Góra, Poland, September 5-7, 2018
EditorsKatarzyna Arkusz, Romuald Bedzinski, Tomasz Klekiel, Szczepan Piszczatowski
Number of pages9
PublisherSpringer
Publication date5 Sept 2018
Edition1
Pages98 - 106
ISBN (Print)978-3-319-97285-5
ISBN (Electronic)978-3-319-97286-2
DOIs
Publication statusPublished - 5 Sept 2018
EventInternational Conference of the Polish Society of Biomechanics - Zielona Góra, Poland
Duration: 5 Sept 20187 Sept 2018

Conference

ConferenceInternational Conference of the Polish Society of Biomechanics
Country/TerritoryPoland
CityZielona Góra
Period05/09/201807/09/2018
SeriesAdvances in Intelligent Systems and Computing
Volume831
ISSN2194-5357

Keywords

  • Musculoskeletal models
  • Running
  • Statistics
  • Principal Component Analysis

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