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A Neuromuscular Interface for Robotic Devices Control.

Innokentiy KastalskiyVasily MironovSergey LobovNadia KrilovaAlexey PimashkinVictor Kazantsev
Published in: Computational and mathematical methods in medicine (2018)
A neuromuscular interface (NI) that can be employed to operate external robotic devices (RD), including commercial ones, was proposed. Multichannel electromyographic (EMG) signal is used in the control loop. Control signal can also be supplemented with electroencephalography (EEG), limb kinematics, or other modalities. The multiple electrode approach takes advantage of the massive resources of the human brain for solving nontrivial tasks, such as movement coordination. Multilayer artificial neural network was used for feature classification and further to provide command and/or proportional control of three robotic devices. The possibility of using biofeedback can compensate for control errors and implement a fundamentally important feature that has previously limited the development of intelligent exoskeletons, prostheses, and other medical devices. The control system can be integrated with wearable electronics. Examples of technical devices under control of the neuromuscular interface (NI) are presented.
Keyphrases
  • machine learning
  • neural network
  • deep learning
  • working memory
  • emergency department
  • robot assisted
  • functional connectivity
  • heart rate
  • patient safety
  • resting state