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Related Experiment Videos

Automatic tuning of myoelectric prostheses

C Bonivento1, A Davalli, C Fantuzzi

  • 1University of Bologna, Italy. cbonivento@deis.unibo.it

Journal of Rehabilitation Research and Development
|August 15, 1998
PubMed
Summary

This study introduces the Microprocessor Controlled Arm (MCA) Auto Tuning software, utilizing Fuzzy Logic Expert Systems (FLES) to automate myoelectric prosthesis calibration. This innovation simplifies prosthesis tuning for users and technicians, reducing costs and improving service quality.

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Area of Science:

  • Biomedical Engineering
  • Artificial Intelligence
  • Rehabilitation Technology

Background:

  • Myoelectric prostheses require precise control parameter tuning for optimal function.
  • Current tuning procedures are time-consuming, require expert technicians, and are inconvenient for users.
  • Variability in myoelectric signals necessitates frequent recalibration, posing a challenge for prosthesis maintenance.

Purpose of the Study:

  • To develop an automated software package for tuning myoelectric prostheses.
  • To translate expert operator heuristics into a Fuzzy Logic Expert System (FLES) knowledge base.
  • To create a user-friendly tool that empowers both expert operators and unskilled individuals in prosthesis calibration.

Main Methods:

  • Development of the Microprocessor Controlled Arm (MCA) Auto Tuning software package.

Related Experiment Videos

  • Integration of Fuzzy Logic Expert Systems (FLES) to capture and apply expert knowledge.
  • Implementation of a graphical user interface for guided, step-by-step parameter tuning.
  • Utilizing myoelectric signals from skin-surface electrodes to control the artificial limb.

    • Main Results:

    • The MCA Auto Tuning software successfully emulates the traditional expert-aided tuning procedure.
    • The system significantly reduces the time required for prosthesis parameter setup for both users and technicians.
    • The software facilitates parameter adjustments, accommodating variations in myoelectric signals.

    Conclusions:

    • The MCA Auto Tuning package offers a practical and efficient solution for myoelectric prosthesis calibration.
    • Widespread adoption can lead to substantial economic benefits and enhanced service quality for prosthesis users.
    • The software democratizes prosthesis tuning, making it accessible to individuals without specialized technical knowledge.