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Brain Activity Reflects Subjective Response to Delayed Input When Using an Electromyography-Controlled Robot.

Hyeonseok Kim1,2, Yeongdae Kim3, Makoto Miyakoshi2

  • 1Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan.

Frontiers in Systems Neuroscience
|December 16, 2021
PubMed
Summary

This study explored how subjective delay perception affects brain activity during electromyography (EMG) robot control. We found distinct theta band activity in the parietal lobe when users couldn't perceive added delays, crucial for adaptive system design.

Keywords:
delayelectroencephalogram (EEG)electromyography (EMG)independent componentparietalrobotrobot handsubjective response

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Area of Science:

  • Neuroscience
  • Robotics
  • Human-Computer Interaction

Background:

  • Electromyography (EMG) signals are used for robot control, but intrinsic parameters complicate user understanding.
  • System response time variability necessitates investigating subjective delay perception independent of actual system delay.

Purpose of the Study:

  • To investigate the influence of subjective delay perception on brain activation during EMG-based robot hand control.
  • To identify neural correlates associated with the user's ability to perceive introduced delays.

Main Methods:

  • Participants controlled a robot hand using EMG signals with muscle synergy for grip commands.
  • Four delay durations (0 ms, 50 ms, 125 ms, 250 ms) were applied, and participants reported their perception of the delay.
  • Brain activity was recorded and compared between trials where participants were 'sure' or 'not sure' about the delay.

Main Results:

  • A significant difference in theta band power within the parietal lobe was observed.
  • This neural activity pattern correlated with the time interval where subjects could not discern the introduced delay.

Conclusions:

  • Subjective delay perception, particularly the inability to detect it, is linked to specific brain activation patterns in the theta band of the parietal lobe.
  • Findings offer critical insights for developing and evaluating the usability of adaptive robotic systems controlled by EMG signals.