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Measurement of foot placement and its variability with inertial sensors

机译:用惯性传感器测量脚的位置及其变化

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Gait parameters such as stride length, width, and period, as well as their respective variabilities, are widely used as indicators of mobility and walking function. Foot placement and its variability have thus been applied in areas such as aging, fall risk, spinal cord injury, diabetic neuropathy, and neurological conditions. But a drawback is that these measures are presently best obtained with specialized laboratory equipment such as motion capture systems and instrumented walkways, which may not be available in many clinics and certainly not during daily activities. One alternative is to fix inertial measurement units (IMUs) to the feet or body to gather motion data. However, few existing methods measure foot placement directly, due to drift associated with inertial data. We developed a method to measure stride-to-stride foot placement in unconstrained environments, and tested whether it can accurately quantify gait parameters over long walking distances. The method uses ground contact conditions to correct for drift, and state estimation algorithms to improve estimation of angular orientation. We tested the method with healthy adults walking over-ground, averaging 93 steps per trial, using a mobile motion capture system to provide reference data. We found IMU estimates of mean stride length and duration within 1% of motion capture, and standard deviations of length and width within 4% of motion capture. Step width cannot be directly estimated by IMUs, although lateral stride variability can. Inertial sensors measure walks over arbitrary distances, yielding estimates with good statistical confidence. Gait can thus be measured in a variety of environments, and even applied to long-term monitoring of everyday walking.
机译:步态参数(例如步幅,宽度和周期以及它们各自的变异性)被广泛用作移动性和步行功能的指标。因此,脚的放置及其可变性已被应用在诸如衰老,跌倒风险,脊髓损伤,糖尿病性神经病变和神经系统疾病等领域。但是缺点是,这些措施目前最好通过专用的实验室设备(例如运动捕捉系统和仪器化的人行道)来获得,这些设备在许多诊所中可能无法使用,当然在日常活动中也可能无法使用。一种替代方法是将惯性测量单位(IMU)固定在脚或身体上,以收集运动数据。但是,由于与惯性数据相关的漂移,很少有现有方法直接测量脚的位置。我们开发了一种在不受限制的环境中测量跨步脚步放置的方法,并测试了它是否可以在长距离行走时准确地量化步态参数。该方法使用地面接触条件来校正漂移,并使用状态估计算法来改善角度方向的估计。我们用健康的成年人在地面上行走测试了该方法,每次试验平均使用了93个步骤,并使用了移动运动捕捉系统来提供参考数据。我们发现IMU估计平均步幅的长度和持续时间在运动捕捉的1%以内,长度和宽度的标准偏差在运动捕捉的4%以内。尽管横向步幅可变,但步距不能由IMU直接估算。惯性传感器可测量任意距离上的步行,并具有良好的统计置信度。因此,可以在各种环境中测量步态,甚至可以将步态应用于日常步行的长期监测。

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