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Sensitivity comparison of inertial to optical motion capture during gait: implications for tracking recovery

机译:步态期间惯性与光学运动捕获的灵敏度比较:对跟踪恢复的意义

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Wearable sensors provide a foundation for development of wearable robotic technology to be used in clinical applications. Inertial motion capture (IMC) has emerged as a viable alternative to more cumbersome, non-portable optical methods. Previous work has validated the accuracy of IMC for gait compared to optical motion capture (OMC). However, it is unclear how well IMC can measure the small changes in gait function needed to gauge recovery. In this study, we evaluate the sensitivity of IMC compared to OMC to small changes in gait on a cohort of unimpaired individuals during treadmill walking. Eight individuals walked on a split-belt treadmill in three-minute trials with five randomized conditions: right belt speed decrementing at 0.05 m/s from 1.0 m/s, all with left belt held at 1.0 m/s, simulating recovery of hemiparetic gait. We extracted the root mean square deviation (RMSD) of joint kinematics between limbs and within the limb with modulated gait speed as the main outcome measure. We used linear mixed models to identify differences in sensitivity to changes in gait asymmetry and gait speed. Based on these models, we estimated the minimal detectible interval in gait parameters. We found that IMC was capable of measuring a difference in gait speed of 0.08 m/s, roughly the equivalent of two weeks recovery progress. Statistically we could not conclude a difference of sensitivity between IMC and OMC, although there is a strong trend that IMC is more sensitive to changes in gait. We conclude that IMC is a valid tool to measure progress in gait kinematics over the course of recovery.
机译:可穿戴式传感器为用于临床应用的可穿戴机器人技术的发展奠定了基础。惯性运动捕捉(IMC)已成为替代更麻烦,不可携带的光学方法的可行替代方案。与光学运动捕获(OMC)相比,先前的工作已经验证了IMC在步态上的准确性。但是,尚不清楚IMC能够如何很好地测量步态功能的微小变化以衡量恢复能力。在这项研究中,我们评估了IMC与OMC相比在跑步机行走过程中对一群弱势人群步态细微变化的敏感性。在五分钟的随机条件下,八个人在三分钟试验中在皮带分离式跑步机上行走:右皮带速度从1.0 m / s降低0.05 m / s,所有左皮带速度保持在1.0 m / s,模拟了偏瘫步态的恢复。我们提取了肢体之间和肢体内关节运动学的均方根偏差(RMSD),将步态速度调节为主要结果。我们使用线性混合模型来识别对步态不对称性和步态速度变化的敏感性差异。基于这些模型,我们估计了步态参数的最小可检测间隔。我们发现,IMC能够测量步态速度差异0.08 m / s,大致相当于两周的恢复进度。从统计学上讲,尽管IMC对步态的变化更为敏感,但仍无法得出IMC与OMC之间灵敏度的差异。我们得出的结论是,IMC是衡量恢复过程中步态运动学进展的有效工具。

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