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Related Experiment Video

Updated: May 22, 2026

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
06:58

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

Multigesture Electromyographic Control Complexity in Upper Limb Prostheses Actuated via Single Sensor Input

Abrianna Lalle1, Samantha Migliore1, Jeffrey Stevenson1

  • 1Limbitless Solutions, University of Central Florida, Orlando, FL, United States.

JMIR Rehabilitation and Assistive Technologies
|May 20, 2026
PubMed
Summary

Learning three electromyography (EMG) gestures progressively improves prosthetic control, balancing device capability with user needs. This approach enhances usability and manages cognitive workload for EMG upper limb prostheses.

Keywords:
artificial limbsbiomedical engineeringbiomedical technologygamified trainingprosthesesupper limb prosthesisusabilityuser centered design

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Last Updated: May 22, 2026

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Area of Science:

  • Biomedical Engineering
  • Rehabilitation Technology
  • Human-Computer Interaction

Background:

  • High prosthetic rejection rates are linked to functional limitations.
  • Electromyography (EMG) upper limb prostheses use residual limb muscle contractions for control.
  • Expanding EMG prostheses to multigesture control presents challenges in accuracy, usability, training time, and cognitive load.

Purpose of the Study:

  • To assess the feasibility of learning multiple EMG gestures in a single training session.
  • To investigate the impact of increasing gesture complexity on user performance, usability, and cognitive workload.

Main Methods:

  • Participants (n=54) with intact upper extremities were fitted with a surface EMG device (Flex Controller).
  • A custom training app presented 1, 3, or 5 control zones, each corresponding to a specific prosthesis gesture.
  • Outcomes measured included task performance, perceived usability (System Usability Scale), and cognitive workload (NASA-Task Load Index).

Main Results:

  • Task performance significantly decreased as the number of control zones increased (P<.001).
  • Perceived usability was rated lower by the 5-gesture cohort compared to a progressive training group (P=.05).
  • Cognitive workload and perceived difficulty increased with a higher number of gestures.

Conclusions:

  • Progressive training for three EMG gestures is feasible and recommended.
  • A three-gesture progressive learning approach balances device functionality, user intention, perceived usability, and cognitive demands.
  • This method optimizes the user experience for advanced EMG upper limb prostheses.