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将肌肉骨骼力学生物学与个体相连接以用于训练和康复的仿生技术。

Bioinspired Technologies to Connect Musculoskeletal Mechanobiology to the Person for Training and Rehabilitation.

作者信息

Pizzolato Claudio, Lloyd David G, Barrett Rod S, Cook Jill L, Zheng Ming H, Besier Thor F, Saxby David J

机构信息

School of Allied Health Sciences, Griffith University, Gold Coast, QLD, Australia.

Gold Coast Orthopaedic Research and Education Alliance, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia.

出版信息

Front Comput Neurosci. 2017 Oct 18;11:96. doi: 10.3389/fncom.2017.00096. eCollection 2017.

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 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.

摘要

肌肉骨骼组织通过合成代谢适应对最佳机械信号(如应变)做出反应,而高于和低于最佳水平的机械信号会导致组织分解代谢。如果能够改变个体的身体行为,以产生针对肌肉骨骼组织的最佳机械信号,那么有针对性的强化和/或修复将成为可能。我们提出了新的受生物启发的技术,以提供相关机械信号的实时生物反馈,从而指导训练和康复。在这篇综述中,我们描述了可穿戴设备如何与肌肉骨骼组织的计算刚体和连续体模型结合使用,以实时估计局部组织应力和应变。有人提出,这些受生物启发的技术将促进一种新的体育训练方法,即通过最佳的组织负荷来促进组织强化和/或修复。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3223/5651250/db1bd2950eef/fncom-11-00096-g0001.jpg

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