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A Neuromuscular Interface for Robotic Devices Control.

Innokentiy Kastalskiy1, Vasily Mironov1, Sergey Lobov1

  • 1Center for Translational Technologies, Nizhny Novgorod Neuroscience Center, National Research Lobachevsky State University of Nizhny Novgorod, Gagarin Ave. 23, Nizhny Novgorod 603950, Russia.

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Summary
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A novel neuromuscular interface (NI) uses electromyographic (EMG) signals and artificial neural networks to control robotic devices. This technology enhances movement coordination and aids in developing advanced medical devices like exoskeletons and prostheses.

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Area of Science:

  • Biomedical Engineering
  • Neuroscience
  • Robotics

Background:

  • Operating external robotic devices (RD) requires sophisticated control systems.
  • Existing control methods for intelligent medical devices face limitations in movement coordination and error compensation.

Purpose of the Study:

  • To propose a novel neuromuscular interface (NI) for controlling external robotic devices.
  • To integrate multichannel electromyographic (EMG) signals and artificial neural networks for enhanced control.
  • To explore the use of supplementary data like electroencephalography (EEG) and limb kinematics.

Main Methods:

  • Utilized multichannel electromyographic (EMG) signals within the control loop.
  • Employed a multilayer artificial neural network for feature classification and control command generation.
  • Investigated the integration of biofeedback to compensate for control errors.

Main Results:

  • Successfully demonstrated control of three robotic devices using the proposed neuromuscular interface.
  • The system leverages the human brain's resources for complex movement coordination.
  • Biofeedback integration showed potential to overcome limitations in intelligent exoskeleton and prosthesis development.

Conclusions:

  • The developed neuromuscular interface offers a viable method for operating robotic devices, including commercial ones.
  • This technology can significantly advance the development of intelligent exoskeletons, prostheses, and other medical devices.
  • Integration with wearable electronics and supplementary control modalities like EEG is feasible.