A Review of Computer Simulation of Spine Biomechanics for the Treatment of Scoliosis

Athena Jalalian, Ian Gibson, Eng Hock Tay, Gabriel Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

This paper reviews the biomechanical computer models of spine and scoliosis and their roles in provision of predictive information for surgeons and clinicians. The review examines the modeling schemes, multi-body modeling (MBM) and finite element modeling (FEM), utilized for spine modeling, models of the spine components and the validation processes. It reveals that the available models help clinicians have a priori choice of correction techniques and demonstrate to patients the expected degree of correction. Advantageously, the models can enhance understanding of the spine by simulating its behavior in different conditions and situations, and provide information that cannot be easily obtained through in vivo and in vitro experimental studies. Mostly, FEM has been employed in scoliotic spine modeling, while MBM has been seldom used despite having many advantages over FEM. The models are generally developed and validated through modifying the parameters and matching the model behavior with experimental kinematic data.
Original languageEnglish
Title of host publicationThe 5th TSME International Conference on Mechanical Engineering
Subtitle of host publication17-19th December 2014, The Empress, Chiang Mai
PublisherThai Society of Mechanical Engineers (TSME)
Pages72-72
Number of pages1
Publication statusPublished - 2014
Externally publishedYes
Event5th TSME International Conference on Mechanical Engineering, TSME-ICoME 2014 - Chiang Mai, Thailand
Duration: 17 Dec 201419 Dec 2014
Conference number: 5

Conference

Conference5th TSME International Conference on Mechanical Engineering, TSME-ICoME 2014
Abbreviated titleTSME-ICoME 2014
CountryThailand
CityChiang Mai
Period17/12/1419/12/14

Keywords

  • Scoliosis
  • Scoliotic spine
  • Multi-body modeling
  • Finite element modeling

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