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首页> 外文期刊>Biomedical and Health Informatics, IEEE Journal of >Effect of Cadence Regulation on Muscle Activation Patterns During Robot-Assisted Gait: A Dynamic Simulation Study
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Effect of Cadence Regulation on Muscle Activation Patterns During Robot-Assisted Gait: A Dynamic Simulation Study

机译:步态调节对机器人辅助步态过程中肌肉激活模式的影响:动态仿真研究

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摘要

Cadence or stride frequency is an important parameter being controlled in gait training of neurologically impaired subjects. The aim of this study was to examine the effects of cadence variation on muscle activation patterns during robot-assisted unimpaired gait using dynamic simulations. A 2-D musculoskeletal model of human gait was developed considering eight major muscle groups along with an existing ground contact force model. A 2-D model of a robotic orthosis was also developed that provides actuation to the hip, knee, and ankle joints in the sagittal plane to guide subject's limbs on reference trajectories. A custom inverse dynamics algorithm was used along with a quadratic minimization algorithm to obtain a feasible set of muscle activation patterns. Predicted patterns of muscle activations during slow, natural, and fast cadence were compared and the mean muscle activations were found to be increasing with an increase in cadence. The proposed dynamic simulation provides important insight into the muscle activation variations with change in cadence during robot-assisted gait and provides the basis for investigating the influence of cadence regulation on neuromuscular parameters of interest during robot-assisted gait.
机译:步频或步幅频率是在神经功能障碍受试者的步态训练中要控制的重要参数。这项研究的目的是使用动态模拟研究步频变化对机器人辅助无障碍步态期间肌肉激活模式的影响。考虑到八个主要的肌肉群以及现有的地面接触力模型,开发了一种人的步态的二维肌肉骨骼模型。还开发了一种机器人矫形器的二维模型,该模型可在矢状面内对髋,膝和踝关节进行驱动,以在参考轨迹上引导受试者的四肢。使用自定义逆动力学算法以及二次最小化算法来获得一组可行的肌肉激活模式。比较了慢,自然和快节奏中肌肉激活的预测模式,发现平均肌肉激活随着节奏的增加而增加。拟议的动态仿真提供了重要的洞察力,随着步态的变化,在机器人辅助步态的肌肉激活变化,并提供基础研究步态调节对机器人辅助步态感兴趣的神经肌肉参数的基础。

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