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Learning an EMG Controlled Game: Task-Specific Adaptations and Transfer.

Ludger van Dijk1, Corry K van der Sluis2, Hylke W van Dijk3

  • 1University of Groningen, University Medical Center Groningen, Center for Human Movement Science, Groningen, The Netherlands.

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|August 25, 2016
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Summary
This summary is machine-generated.

Myoelectric games (myogames) improve EMG control for specific tasks but do not transfer to prosthesis simulation. Further research is needed to enhance skill generalization for amputees.

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Area of Science:

  • Rehabilitation robotics
  • Human-computer interaction
  • Neuroprosthetics

Background:

  • Myoelectric games (myogames) are increasingly used in upper limb amputation rehabilitation.
  • Evidence for their effectiveness in improving prosthetic control skills is limited.

Purpose of the Study:

  • To investigate if myogaming enhances electromyography (EMG) control.
  • To determine if improvements in myogaming transfer to prosthesis-simulator tasks.

Main Methods:

  • 28 able-bodied participants were divided into a myogaming group (Breakout-EMG) and a control group (Mario game).
  • Training involved 20 minutes daily for 4 days, using wrist flexor/extensor myosignals for game control.
  • Pre- and post-training assessments included game performance and a prosthesis-simulator task.

Main Results:

  • The myogaming group showed significantly greater in-game accuracy improvement compared to controls.
  • Increased adaptation of EMG signals to the game was observed in the myogaming group.
  • No significant differences were found between groups in the prosthesis-simulator task performance.

Conclusions:

  • Myogames effectively improve task-specific myoelectric control skills.
  • Transfer of these skills to prosthesis control tasks is not straightforward and requires further investigation.
  • Future myogame designs should consider strategies to promote broader skill generalization.