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  • Bioinspired technologies to connect musculoskeletal mechanobiology to the person for training and rehabilitation

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    PizzolatoPUB2646.pdf (1.372Mb)
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    Version of Record (VoR)
    Author(s)
    Pizzolato, Claudio
    Lloyd, David G
    Barrett, Rod S
    Cook, Jill L
    Zheng, Ming H
    Besier, Thor F
    Saxby, David J
    Griffith University Author(s)
    Barrett, Rod
    Lloyd, David
    Saxby, David J.
    Pizzolato, Claudio
    Year published
    2017
    Metadata
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    Abstract
    Musculoskeletal tissues respond to optimal mechanical signals (e.g., strains) through anabolic adaptations, while mechanical signals above and below optimal levels cause tissue catabolism. If an individual's physical behavior could be altered to generate optimal mechanical signaling to musculoskeletal tissues, then targeted strengthening and/or repair would be possible. We propose new bioinspired technologies to provide real-time biofeedback of relevant mechanical signals to guide training and rehabilitation. In this review we provide a description of how wearable devices may be used in conjunction with computational rigid-body ...
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    Musculoskeletal tissues respond to optimal mechanical signals (e.g., strains) through anabolic adaptations, while mechanical signals above and below optimal levels cause tissue catabolism. If an individual's physical behavior could be altered to generate optimal mechanical signaling to musculoskeletal tissues, then targeted strengthening and/or repair would be possible. We propose new bioinspired technologies to provide real-time biofeedback of relevant mechanical signals to guide training and rehabilitation. In this review we provide a description of how wearable devices may be used in conjunction with computational rigid-body and continuum models of musculoskeletal tissues to produce real-time estimates of localized tissue stresses and strains. It is proposed that these bioinspired technologies will facilitate a new approach to physical training that promotes tissue strengthening and/or repair through optimal tissue loading.
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    Journal Title
    Frontiers in Computational Neuroscience
    Volume
    11
    DOI
    https://doi.org/10.3389/fncom.2017.00096
    Copyright Statement
    © 2017 Pizzolato, Lloyd, Barrett, Cook, Zheng, Besier and Saxby. 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) or licensor 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.
    Subject
    Clinical sciences
    Biomechanics
    Neurosciences
    Publication URI
    http://hdl.handle.net/10072/356098
    Collection
    • Journal articles

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