Determining the Marker Configuration and Modeling Technique to Optimize the Biomechanical Analysis of Running-Specific Prostheses

Abstract

The purpose of this study was to develop and validate a model with optimal set-up of reflective markers, producing minimal errors in inverse dynamics calculations. The Statement of Work for this project indicated two specific aims. Specific Aim 1 proposed to develop and validate a model with unique optimal marker placements for specific running prosthesis designs. The proposed timeline indicated that preparation for the experimental setting and formulation of the program for data analysis would occur during Months 1-8. These milestones were reached on schedule. During Months 8-16, we proposed to complete MTS testing, begin validating the general model, and begin analyzing the MTS data to determine the final marker model for each running-specific prosthesis. Some of these milestones were delayed due to procurement issues arising from the prosthesis manufacturers. A no-cost extension until 28 February 2012 was granted due to these issues. These milestones were completed as anticipated upon prosthesis procurement. The results of this study indicate that marker placement and number of markers on a running-specific prosthesis did not greatly influence the accuracy of kinetic data of the running prosthesis designs tested. A draft of a manuscript detailing the study results is included as an Appendix to this report.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2011
Accession Number
ADA626511

Entities

People

  • Adam Hsieh
  • Alison Linberg
  • Erik Wolf
  • Jae K. Shim

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Amputees
  • Data Analysis
  • Dynamics
  • Errors
  • Joints (Anatomy)
  • Load Cells
  • Lower Extremity
  • Lower Limb Amputations
  • Lower Limb Prostheses
  • Motion Capture
  • Procurement
  • Prostheses And Implants
  • Prosthesis Fitting
  • Prosthetics
  • Residual Limbs
  • Surgical Amputations
  • Three Dimensional

Readers

  • Clinical Trial Research.
  • Computational Modeling and Simulation

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference