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Moving-window dynamic optimization: design of stimulation profiles for walking.

Strahinja Dosen1, Dejan B Popović

  • 1Center for Sensory Motor Interaction, Aalborg University, Aalborg 9220, Denmark. sdosen@hst.aau.dk

IEEE Transactions on Bio-Medical Engineering
|February 11, 2009
PubMed
Summary

This study introduces a new simulation using moving-window dynamic optimization (MWDO) to improve control for electrical stimulation-based walking assistance in hemiplegic individuals. The MWDO algorithm efficiently determines optimal muscle stimulation profiles for restoring natural gait patterns.

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Area of Science:

  • Biomedical Engineering
  • Rehabilitation Technology
  • Neuroscience

Background:

  • Hemiplegic gait is characterized by impaired motor control and balance.
  • Electrical stimulation offers a promising avenue for restoring walking function.
  • Current control strategies for functional electrical stimulation (FES) require optimization.

Purpose of the Study:

  • To develop and validate a simulation for generating optimal control parameters for FES-assisted walking in hemiplegic individuals.
  • To synthesize a rule-base for FES control using a novel optimization algorithm.
  • To analyze the effectiveness of the simulation in determining muscle stimulation profiles for gait restoration.

Main Methods:

  • Development of a moving-window dynamic optimization (MWDO) algorithm.

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  • Simulation of sensor-input to muscle-stimulation-output relationships for walking.
  • Optimization criterion: minimizing tracking errors while penalizing muscle effort.
  • Testing with healthy and hemiplegic gait models and target trajectories.

    • Main Results:

    • The MWDO algorithm successfully generated piecewise constant stimulation intensities.
    • Simulation demonstrated the ability to analyze achievable trajectories for both healthy and hemiplegic models.
    • The MWDO proved efficient in determining stimulation profiles for accurate gait tracking.
    • Outputs showed distinct differences in stimulation needs between healthy and hemiplegic models.

    Conclusions:

    • The MWDO simulation is an effective tool for analyzing gait trajectories and optimizing FES control.
    • This approach facilitates the development of personalized FES strategies for hemiplegic individuals.
    • The simulation aids in understanding the relationship between muscle stimulation and gait recovery.