首页> 美国卫生研究院文献>Journal of Biomechanical Engineering >Electromyography-Driven Forward Dynamics Simulation to Estimate In Vivo Joint Contact Forces During Normal Smooth and Bouncy Gaits
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Electromyography-Driven Forward Dynamics Simulation to Estimate In Vivo Joint Contact Forces During Normal Smooth and Bouncy Gaits

机译:肌电图驱动的前向动力学仿真以估计正常平滑和弹性步态期间的体内关节接触力

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摘要

Computational models that predict in vivo joint loading and muscle forces can potentially enhance and augment our knowledge of both typical and pathological gaits. To adopt such models into clinical applications, studies validating modeling predictions are essential. This study created a full-body musculoskeletal model using data from the “Sixth Grand Challenge Competition to Predict in vivo Knee Loads.” This model incorporates subject-specific geometries of the right leg in order to concurrently predict knee contact forces, ligament forces, muscle forces, and ground contact forces. The objectives of this paper are twofold: (1) to describe an electromyography (EMG)-driven modeling methodology to predict knee contact forces and (2) to validate model predictions by evaluating the model predictions against known values for a patient with an instrumented total knee replacement (TKR) for three distinctly different gait styles (normal, smooth, and bouncy gaits). The model integrates a subject-specific knee model onto a previously validated generic full-body musculoskeletal model. The combined model included six degrees-of-freedom (6DOF) patellofemoral and tibiofemoral joints, ligament forces, and deformable contact forces with viscous damping. The foot/shoe/floor interactions were modeled by incorporating shoe geometries to the feet. Contact between shoe segments and the floor surface was used to constrain the shoe segments. A novel EMG-driven feedforward with feedback trim motor control strategy was used to concurrently estimate muscle forces and knee contact forces from standard motion capture data collected on the individual subject. The predicted medial, lateral, and total tibiofemoral forces represented the overall measured magnitude and temporal patterns with good root-mean-squared errors (RMSEs) and Pearson's correlation (p2). The model accuracy was high: medial, lateral, and total tibiofemoral contact force RMSEs = 0.15, 0.14, 0.21 body weight (BW), and (0.92 < p2 < 0.96) for normal gait; RMSEs = 0.18 BW, 0.21 BW, 0.29 BW, and (0.81 < p2 < 0.93) for smooth gait; and RMSEs = 0.21 BW, 0.22 BW, 0.33 BW, and (0.86 < p2 < 0.95) for bouncy gait, respectively. Overall, the model captured the general shape, magnitude, and temporal patterns of the contact force profiles accurately. Potential applications of this proposed model include predictive biomechanics simulations, design of TKR components, soft tissue balancing, and surgical simulation.
机译:预测体内关节负荷和肌肉力量的计算模型可以潜在地增强和增强我们对典型步态和病理步态的了解。为了将此类模型用于临床应用,验证模型预测的研究必不可少。这项研究使用“第六届大挑战赛预测体内膝盖负荷”的数据创建了一个全身肌肉骨骼模型。该模型结合了右腿的特定对象几何形状,以便同时预测膝盖接触力,韧带力,肌肉力和地面接触力。本文的目标有两个:(1)描述一种由肌电图(EMG)驱动的建模方法,以预测膝盖的接触力;(2)通过针对具有仪器仪表的患者的已知值评估模型预测值来验证模型预测值三种明显不同的步态样式(正常,平滑和弹性步态)的膝关节置换(TKR)。该模型将特定于受试者的膝盖模型集成到先前已验证的通用全身肌肉骨骼模型上。组合模型包括六个自由度(6DOF)em股和胫股关节,韧带力和带有粘性阻尼的可变形接触力。脚/鞋子/地板的相互作用是通过将鞋子的几何形状合并到脚上来建模的。鞋段和地板表面之间的接触用于约束鞋段。一种新颖的具有反馈微调电机控制策略的EMG驱动的前馈用于根据从个体受试者收集的标准运动捕获数据同时估算肌肉力和膝盖接触力。预测的内侧,外侧和总胫股力量代表总体测得的幅度和时间模式,具有良好的均方根误差(RMSE)和皮尔森相关性(p 2 )。模型的准确性很高:正常步态时,内侧,外侧和总胫股接触力RMSEs = 0.15、0.14、0.21体重(BW)和(0.92 2 <0.96); RMSEs == 0.18 BW,0.21 BW,0.29 BW和(0.81 2 <0.93),步态流畅;弹性步态的均方根和均方根误差分别为0.21 BW,0.22 BW,0.33 BW和(0.86 2 <0.95)。总体而言,该模型准确地捕获了接触力曲线的一般形状,大小和时间模式。该提议模型的潜在应用包括预测性生物力学模拟,TKR组件的设计,软组织平衡和手术模拟。

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