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首页> 外文期刊>Journal of Biomechanical Science and Engineering >An Inverse Dynamic Approach for Quantitative Muscle Force Estimation during Human Standing-Up Process
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An Inverse Dynamic Approach for Quantitative Muscle Force Estimation during Human Standing-Up Process

机译:人体站立过程中肌肉力量定量估计的逆动态方法

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References(20) As it is inconvenient to directly measure tension forces of muscles attaching on limbs, an inverse dynamic approach for quantitative muscle force estimation during human standing-up process was developed. In the standing-up experiment, a rehabilitation robot was used for offering assistance and measuring dynamic parameters of body segments. Ground reaction force (GRF) and center of pressure (COP) of human body, rotational motions of trunk, thigh and shank were real-time measured by the sensors of the robot system. Meanwhile, the AnyBody Modeling System was adopted for calculating muscle forces of lower limbs. In AnyBody Modeling System, a musculoskeletal model composed of thigh, shank, foot, four joints and fifteen muscles was developed. The GRF, COP and motion data measured with sensors were imported into the model, and then the tension forces of muscles of lower limb were calculated through an inverse dynamics method. Furthermore for the validation of the rehabilitation experiment, the activation levels of muscles were also directly measured by an electromyography (EMG) system, and the calculated AnyBody results matched the measured EMG results. Therefore, this muscle force estimation approach appears to be practical for determining muscle forces in the musculoskeletal analysis of human limbs.
机译:参考文献(20)由于直接测量附着在四肢上的肌肉的拉力不方便,因此开发了一种逆向动力学方法,用于估计人体站立过程中的肌肉力。在站立实验中,康复机器人被用来提供帮助并测量身体各部分的动态参数。机器人系统的传感器实时测量人体的地面反作用力(GRF)和压力中心(COP),躯干,大腿和小腿的旋转运动。同时,采用了AnyBody建模系统来计算下肢的肌肉力量。在AnyBody建模系统中,开发了由大腿,小腿,脚,四个关节和十五个肌肉组成的肌肉骨骼模型。将传感器测量的GRF,COP和运动数据导入模型,然后通过逆动力学方法计算下肢肌肉的拉力。此外,为了验证康复实验,还通过肌电图(EMG)系统直接测量了肌肉的激活水平,并且计算出的AnyBody结果与测量到的EMG结果相匹配。因此,这种肌肉力量估计方法似乎对于确定人体四肢的肌肉骨骼分析中的肌肉力量很实用。

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