Addressing unpredictability may be the key to improving performance with current clinically prescribed myoelectric...

Area of Science:

• Biomedical Engineering
• Rehabilitation Science
• Human-Computer Interaction

Background:

• Upper-limb myoelectric prostheses rely on an efferent control chain involving signal generation, acquisition, and device response.
• Understanding factors influencing user performance is crucial for advancing prosthetic technology and clinical integration.

Purpose of the Study:

• To determine the relative impact of signal generation skill, signal acquisition predictability, and device response (electromechanical delay) on myoelectric prosthesis user performance.
• To identify key factors for guiding future prosthetic control system development.

Main Methods:

• Collected data from twenty trans-radial prosthesis users with their prescribed devices.
• Assessed signal generation via reaction times and signal tracking.
• Evaluated signal acquisition predictability using reaction time spread and undesired hand activations.
• Measured device response through electromechanical delay.

Main Results:

• Abstract measures of muscle signal generation skill showed poor correlation with user performance.
• Undesired hand activations and incorrect responses correlated with kinematics and gaze measures, highlighting unpredictability as a key factor.
• Longer electromechanical delays unexpectedly correlated with better performance, contrary to initial hypotheses.

Conclusions:

• Prosthetic control performance is more influenced by the predictability of signal acquisition than by the user's skill in generating muscle signals.
• Future research should investigate the sources of unpredictability in myoelectric control and develop interventions to mitigate their impact on user functionality.