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Neurorehabilitation robotics: how much control should therapists have?

Robotic technologies for rehabilitating motor impairments from neurological injuries have been the focus of intensive research and capital investment for more than 30 years. However, these devices have failed to convincingly demonstrate greater restoration of patient function compared to conventiona...

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Autores principales: Hasson, Christopher J., Manczurowsky, Julia, Collins, Emily C., Yarossi, Mathew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10213717/
https://www.ncbi.nlm.nih.gov/pubmed/37250692
http://dx.doi.org/10.3389/fnhum.2023.1179418
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author Hasson, Christopher J.
Manczurowsky, Julia
Collins, Emily C.
Yarossi, Mathew
author_facet Hasson, Christopher J.
Manczurowsky, Julia
Collins, Emily C.
Yarossi, Mathew
author_sort Hasson, Christopher J.
collection PubMed
description Robotic technologies for rehabilitating motor impairments from neurological injuries have been the focus of intensive research and capital investment for more than 30 years. However, these devices have failed to convincingly demonstrate greater restoration of patient function compared to conventional therapy. Nevertheless, robots have value in reducing the manual effort required for physical therapists to provide high-intensity, high-dose interventions. In most robotic systems, therapists remain outside the control loop to act as high-level supervisors, selecting and initiating robot control algorithms to achieve a therapeutic goal. The low-level physical interactions between the robot and the patient are handled by adaptive algorithms that can provide progressive therapy. In this perspective, we examine the physical therapist's role in the control of rehabilitation robotics and whether embedding therapists in lower-level robot control loops could enhance rehabilitation outcomes. We discuss how the features of many automated robotic systems, which can provide repeatable patterns of physical interaction, may work against the goal of driving neuroplastic changes that promote retention and generalization of sensorimotor learning in patients. We highlight the benefits and limitations of letting therapists physically interact with patients through online control of robotic rehabilitation systems, and explore the concept of trust in human-robot interaction as it applies to patient-robot-therapist relationships. We conclude by highlighting several open questions to guide the future of therapist-in-the-loop rehabilitation robotics, including how much control to give therapists and possible approaches for having the robotic system learn from therapist-patient interactions.
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spelling pubmed-102137172023-05-27 Neurorehabilitation robotics: how much control should therapists have? Hasson, Christopher J. Manczurowsky, Julia Collins, Emily C. Yarossi, Mathew Front Hum Neurosci Human Neuroscience Robotic technologies for rehabilitating motor impairments from neurological injuries have been the focus of intensive research and capital investment for more than 30 years. However, these devices have failed to convincingly demonstrate greater restoration of patient function compared to conventional therapy. Nevertheless, robots have value in reducing the manual effort required for physical therapists to provide high-intensity, high-dose interventions. In most robotic systems, therapists remain outside the control loop to act as high-level supervisors, selecting and initiating robot control algorithms to achieve a therapeutic goal. The low-level physical interactions between the robot and the patient are handled by adaptive algorithms that can provide progressive therapy. In this perspective, we examine the physical therapist's role in the control of rehabilitation robotics and whether embedding therapists in lower-level robot control loops could enhance rehabilitation outcomes. We discuss how the features of many automated robotic systems, which can provide repeatable patterns of physical interaction, may work against the goal of driving neuroplastic changes that promote retention and generalization of sensorimotor learning in patients. We highlight the benefits and limitations of letting therapists physically interact with patients through online control of robotic rehabilitation systems, and explore the concept of trust in human-robot interaction as it applies to patient-robot-therapist relationships. We conclude by highlighting several open questions to guide the future of therapist-in-the-loop rehabilitation robotics, including how much control to give therapists and possible approaches for having the robotic system learn from therapist-patient interactions. Frontiers Media S.A. 2023-05-11 /pmc/articles/PMC10213717/ /pubmed/37250692 http://dx.doi.org/10.3389/fnhum.2023.1179418 Text en Copyright © 2023 Hasson, Manczurowsky, Collins and Yarossi. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Human Neuroscience
Hasson, Christopher J.
Manczurowsky, Julia
Collins, Emily C.
Yarossi, Mathew
Neurorehabilitation robotics: how much control should therapists have?
title Neurorehabilitation robotics: how much control should therapists have?
title_full Neurorehabilitation robotics: how much control should therapists have?
title_fullStr Neurorehabilitation robotics: how much control should therapists have?
title_full_unstemmed Neurorehabilitation robotics: how much control should therapists have?
title_short Neurorehabilitation robotics: how much control should therapists have?
title_sort neurorehabilitation robotics: how much control should therapists have?
topic Human Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10213717/
https://www.ncbi.nlm.nih.gov/pubmed/37250692
http://dx.doi.org/10.3389/fnhum.2023.1179418
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