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Related Experiment Videos

Real-time gait event detection for paraplegic FES walking.

M M Skelly1, H J Chizeck

  • 1Motion Study Laboratory, Cleveland, OH, USA.

IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
|August 3, 2001
PubMed
Summary

A new real-time gait event detection system for paraplegic locomotion using functional electrical stimulation (FES) was developed. This system accurately identifies gait events, enabling adaptive control for improved walking assistance.

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Area of Science:

  • Biomedical Engineering
  • Rehabilitation Technology
  • Neuroprosthetics

Background:

  • Paraplegic locomotion via functional electrical stimulation (FES) requires precise control of stimulation parameters.
  • Real-time detection of gait events is crucial for adaptive FES control but has faced technical limitations.

Purpose of the Study:

  • To develop and evaluate a real-time gait event detection system for paraplegic subjects undergoing FES-assisted locomotion.
  • To improve the accuracy and reliability of gait event timing for closed-loop FES control.

Main Methods:

  • A two-level algorithm processing sensor signals and stimulator patterns was implemented.
  • A fuzzy logic algorithm provided initial gait phase estimates, refined by a second algorithm to determine precise gait event times.

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  • Cosmetically acceptable insole force transducers were utilized for data acquisition.
  • Main Results:

    • The system successfully detected gait events in three subjects with accuracy within approximately half a gait cycle.
    • Detection accuracy remained consistent despite day-to-day variations in gait.
    • Technical and practical issues hindering real-time application were resolved.

    Conclusions:

    • The developed gait event detection system is effective for real-time FES control in paraplegic locomotion.
    • This advancement facilitates automatic adjustment of FES parameters for enhanced walking.
    • The system offers a robust solution for improving FES-assisted mobility.