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Customizing a Cryolite Glass Prosthetic Eye
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Smart Data-Driven Optimization of Powered Prosthetic Ankles Using Surface Electromyography.

Roozbeh Atri1, J Sebastian Marquez2, Connie Leung3

  • 1Human Cyber-Physical Systems Laboratory, Florida International University, Miami, FL 33174, USA. ratri001@fiu.edu.

Sensors (Basel, Switzerland)
|August 22, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces an objective, evidence-based method for tuning powered prosthetic ankles using electromyogram data. The novel approach enhances prosthetic calibration efficiency and accuracy for lower limb amputees.

Keywords:
Latin Hypercube SamplingNelder–Meaddata-driven optimizationelectromyographyparameter tuningpowered prosthetic ankle

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Area of Science:

  • Biomedical Engineering
  • Rehabilitation Technology
  • Prosthetics

Background:

  • Powered prosthetic ankles improve balance and energy efficiency in lower limb amputee gait.
  • Current prosthetic ankle calibration relies on subjective expert observations and experience.
  • Existing tuning methods can be computationally inefficient, requiring extensive parameter searches.

Purpose of the Study:

  • To develop a novel, evidence-based method for objectively tuning powered prosthetic ankles.
  • To improve the time-efficiency and accuracy of prosthetic calibration.
  • To utilize residual limb electromyogram (EMG) data for a data-driven tuning approach.

Main Methods:

  • A model for muscle activity was built using multi-channel electromyogram (EMG) data from the residual limb.
  • A modified Nelder-Mead algorithm combined with Latin Hypercube Sampling was developed for parameter optimization.
  • The modified Nelder-Mead algorithm's performance was compared against exhaustive search, Genetic Algorithm, and conventional Nelder-Mead methods.

Main Results:

  • The modified Nelder-Mead algorithm demonstrated feasibility for objective prosthetic ankle calibration.
  • The proposed method achieved time-efficient tuning compared to exhaustive search.
  • The optimization method successfully calibrated prosthetic ankle parameters using biological evidence.

Conclusions:

  • The presented evidence-based tuning method offers an objective and time-efficient approach to prosthetic ankle calibration.
  • This data-driven optimization technique enhances prosthetic functionality for lower limb amputees.
  • Future research can further refine EMG-based calibration for personalized prosthetic fitting.