Machine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
PLoS One. 2022 Jun 9;17(6):e0269567. doi: 10.1371/journal.pone.0269567. eCollection 2022.
Gait analysis using foot-worn inertial measurement units has proven to be a reliable tool to diagnose and monitor many neurological and musculoskeletal indications. However, only few studies have investigated the robustness of such systems to changes in the sensor attachment and no consensus for suitable sensor positions exists in the research community. Specifically for unsupervised real-world measurements, understanding how the reliability of the monitoring system changes when the sensor is attached differently is from high importance. In these scenarios, placement variations are expected because of user error or personal preferences. In this manuscript, we present the largest study to date comparing different sensor positions and attachments. We recorded 9000 strides with motion-capture reference from 14 healthy participants with six synchronized sensors attached at each foot. Spatial gait parameters were calculated using a double-integration method and compared to the reference system. The results indicate that relevant differences in the accuracy of the stride length exists between the sensor positions. While the average error over multiple strides is comparable, single stride errors and variability parameters differ greatly. We further present a physics model and an analysis of the raw sensor data to understand the origin of the observed differences. This analysis indicates that a variety of attachment parameters can influence the systems' performance. While this is only the starting point to understand and mitigate these types of errors, we conclude that sensor systems and algorithms must be reevaluated when the sensor position or attachment changes.
使用脚部穿戴式惯性测量单元进行步态分析已被证明是一种可靠的工具，可用于诊断和监测许多神经和肌肉骨骼疾病。然而，只有少数研究调查了此类系统对传感器附着变化的稳健性，并且研究界也没有关于合适传感器位置的共识。特别是对于非监督的实际测量，了解当传感器以不同的方式附着时监测系统的可靠性如何变化具有重要意义。在这些情况下，由于用户错误或个人偏好，预计会出现放置变化。在本文中，我们提出了迄今为止最大的研究，比较了不同的传感器位置和附着方式。我们记录了 14 名健康参与者的 9000 步运动捕捉参考数据，每个脚有 6 个同步传感器。使用双积分方法计算空间步态参数，并与参考系统进行比较。结果表明，传感器位置之间存在步长准确性的相关差异。虽然多次跨步的平均误差相当，但单步误差和变异性参数差异很大。我们进一步提出了一个物理模型和对原始传感器数据的分析，以了解观察到的差异的来源。该分析表明，各种附着参数会影响系统的性能。虽然这只是理解和减轻此类错误的起点，但我们得出结论，当传感器位置或附着发生变化时，必须重新评估传感器系统和算法。
