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Inertial sensor based inverse dynamics analysis of human motions

机译:基于惯性传感器的人类运动的逆动力学分析

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Inverse dynamics analysis, which enables the information about joint force/torque of human body from the measured motion data, is a traditional tool in biomechanical studies. Conventionally, measurements of body motion are obtained by motion capture cameras, of which the bulkiness and high cost make it hard to capture some movements that need broad range of space. As an alternative, inertial motion sensing using cheap and small microelectronic mechanical systems (MEMS) based inertial sensors has been proposed. Inertial motion sensing allows ambulatory movement and is also free of occlusion problem. It has been actively studied for recent 2 decades, but until now, most researches have focused on measuring only the kinematics of body segments. In this research, the performance of inertial motion sensing especially aimed at inverse dynamics analysis is studied for squat motion. Kinematic data from inertial motion sensors are used to calculate the normal ground reaction force (GRF), which is evaluated based on the force plate measurement (ground truth) and additionally compared to the estimation result using optical motion sensing system. Squat motion, which can be simply modeled as a 3-segment linkage moving in sagittal plane is targeted. The normal GRF estimation result showed high correlation and low RMSE (R=0.93, RMSE<;0.02 of body weight), which guarantees enough accuracy of inertial motion sensing to be used for estimating joint forces/torques through inverse dynamics analysis about squat.
机译:逆动力学分析,它能够从测量的运动数据中实现有关人体的关节/扭矩的信息,是生物力学研究中的传统工具。通常,通过运动捕获摄像机获得身体运动的测量,其中膨胀和高成本使得难以捕获需要宽范围空间的一些运动。作为一种替代的,已经提出了基于廉价的微电子机械系统(MEMS)的惯性传感器的惯性运动感测。惯性运动感测允许动态运动,也没有闭塞问题。近二十年来,它已经积极研究,但到目前为止,大多数研究都集中在仅测量身体段的运动学。在这项研究中,研究了特别针对逆动力学分析的惯性运动感测的性能进行蹲下运动。来自惯性运动传感器的运动学数据用于计算正常的地面反作用力(GRF),其基于力板测量(接地真理)评估,并使用光学运动传感系统另外与估计结果相比。蹲坐运动,可以简单地建模为在矢状平面中移动的3段连杆。正常GRF估计结果显示出高的相关性和低RMSE(r = 0.93,体重Rmse <; 0.02),其通过关于蹲下的逆动力学分析来估计接合力/扭矩的惯性运动感测的足够精度。

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