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Elucidating Sensorimotor Control Principles with Myoelectric Musculoskeletal Models

机译:用肌电肌肉骨骼模型阐明感觉运动控制原理

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摘要

There is an old saying that you must walk a mile in someone's shoes to truly understand them. This mini-review will synthesize and discuss recent research that attempts to make humans “walk a mile” in an artificial musculoskeletal system to gain insight into the principles governing human movement control. In this approach, electromyography (EMG) is used to sample human motor commands; these commands serve as inputs to mathematical models of muscular dynamics, which in turn act on a model of skeletal dynamics to produce a simulated motor action in real-time (i.e., the model's state is updated fast enough produce smooth motion without noticeable transitions; Manal et al., ). In this mini-review, these are termed myoelectric musculoskeletal models (MMMs). After a brief overview of typical MMM design and operation principles, the review will highlight how MMMs have been used for understanding human sensorimotor control and learning by evoking apparent alterations in a user's biomechanics, neural control, and sensory feedback experiences.
机译:有句老话说,你必须走一英里才能真正了解他们。这份小型综述将综合并讨论最近的研究,这些研究试图使人类在人造肌肉骨骼系统中“行走一英里”,以深入了解控制人类运动控制的原理。在这种方法中,肌电图(EMG)用于对人体运动命令进行采样;这些命令用作肌肉动力学数学模型的输入,而肌肉动力学数学模型又将其作用于骨骼动力学模型以实时产生模拟的运动动作(即,模型的状态更新速度足够快,可以产生平滑的运动,而没有明显的过渡;手动)等)。在本微型审查中,这些被称为肌电肌肉骨骼模型(MMM)。在简要概述了典型的MMM设计和操作原理之后,本文将重点介绍MMM如何通过引起用户生物力学,神经控制和感觉反馈体验方面的明显变化,来用于理解人体感觉运动控制和学习。

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