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A Review of Control Strategies in Closed-Loop Neuroprosthetic Systems.

James Wright1, Vaughan G Macefield2, André van Schaik1

  • 1Biomedical Engineering and Neuroscience, The MARCS Institute, University of Western Sydney Sydney, NSW, Australia.

Frontiers in Neuroscience
|July 28, 2016
PubMed
Summary

Closed-loop neuroprosthetic systems offer better outcomes than open-loop systems due to feedback. This review clarifies control strategies and feedback modes for neuroprosthetic and neurorobotic devices.

Keywords:
brain-machine interfaceclosed-loopcontrol theoryfeedbackneuroprosthetics

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Robotics

Background:

  • Closed-loop neuroprosthetic systems demonstrate superior performance, usability, and embodiment compared to open-loop systems.
  • Effective neuroprosthetics rely on feedback mechanisms for enhanced user outcomes.
  • Interdisciplinary research in neuroprosthetics faces communication challenges due to overlapping terminology.

Purpose of the Study:

  • To review control strategies in experimental, investigational, and clinical neuroprosthetic systems.
  • To establish a baseline understanding of feedback modes and closed-loop controllers.
  • To promote common nomenclature and reduce miscommunication in neuroprosthetic research.

Main Methods:

  • Review of control strategies in Brain Machine Interfaces, neuromodulatory implants, neuroprosthetic systems, and neurorobotic devices.
  • Discussion of feedback control principles and control theory.
  • Examination of diverse feedback approaches in current neuroprosthetic and neurorobotic systems.

Main Results:

  • Closed-loop systems with feedback enhance neuroprosthetic performance and user embodiment.
  • A variety of control strategies are employed across different neuroprosthetic applications.
  • Understanding feedback modes is crucial for optimizing neuroprosthetic system design.

Conclusions:

  • Standardizing nomenclature for control strategies and feedback is essential for advancing neuroprosthetic research.
  • Closed-loop control and effective feedback are key to improving neuroprosthetic functionality.
  • This review provides a foundational understanding for interdisciplinary collaboration in neuroprosthetics.