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A Design Method for FES Bone Health Therapy in SCI.

Brian Andrews1, James Shippen2, Monica Armengol3

  • 1Department of Bio-Engineering at the University of Reading, UK; The Nuffield Department of Surgical Sciences, Oxford.

European Journal of Translational Myology
|January 13, 2017
PubMed
Summary
This summary is machine-generated.

Functional electrical stimulation (FES) may reduce osteoporosis in spinal cord injury (SCI) by stimulating leg bones. This study proposes biomechanical simulation to predict therapy outcomes, optimizing treatments for bone health.

Keywords:
FESFES rowingbone stressosteoporosisspinal cord injury

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Area of Science:

  • Biomechanics
  • Mechano-biology
  • Osteoporosis research

Background:

  • Functional electrical stimulation (FES) activities like walking and cycling are proposed to mitigate osteoporosis in spinal cord injury (SCI) patients by inducing bone-loading forces.
  • Current methods for assessing bone density changes often rely on lengthy, expensive clinical trials with inconsistent results.
  • The specific mechanical stimuli crucial for osteogenesis (bone formation) during FES interventions are frequently not detailed.

Purpose of the Study:

  • To propose a novel design process for predicting clinical outcomes of FES therapies for osteoporosis in SCI.
  • To enable quantitative comparison and optimization of candidate FES-based treatments.
  • To utilize biomechanical simulation and mechano-biology for predicting therapeutic efficacy.

Main Methods:

  • Development of a predictive design process integrating biomechanical simulation and mechano-biology.
  • Application of the proposed method using data from a spinal cord injury patient undergoing rowing exercise with the RowStim (III) system.
  • Analysis of mechanical stimuli applied to leg bones during FES-assisted rowing.

Main Results:

  • The study demonstrates a method to predict clinical outcomes based on biomechanical and mechano-biological principles.
  • Illustrative data from an SCI rower using the RowStim (III) system were analyzed.
  • The approach allows for quantitative assessment of mechanical stimuli relevant to osteogenesis.

Conclusions:

  • A biomechanical simulation and mechano-biology approach can predict the clinical effectiveness of FES therapies for osteoporosis in SCI.
  • This predictive method facilitates optimization and comparison of FES interventions.
  • The proposed design process offers a more efficient alternative to traditional clinical trials for evaluating bone health treatments in SCI.