Department of Biomedical Sciences, University of Sassari, Sassari, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Sassari, Italy.
Insigneo Institute and Department of Mechanical Engineering, University of Sheffield, Sheffield, UK.
J Biomech. 2021 Oct 11;127:110687. doi: 10.1016/j.jbiomech.2021.110687. Epub 2021 Aug 13.
The accurate identification of initial and final foot contacts is a crucial prerequisite for obtaining a reliable estimation of spatio-temporal parameters of gait. Well-accepted gold standard techniques in this field are force platforms and instrumented walkways, which provide a direct measure of the foot-ground reaction forces. Nonetheless, these tools are expensive, non-portable and restrict the analysis to laboratory settings. Instrumented insoles with a reduced number of pressure sensing elements might overcome these limitations, but a suitable method for gait events identification has not been adopted yet. The aim of this paper was to present and validate a method aiming at filling such void, as applied to a system including two insoles with 16 pressure sensing elements (element area = 310 mm), sampling at 100 Hz. Gait events were identified exploiting the sensor redundancy and a cluster-based strategy. The method was tested in the laboratory against force platforms on nine healthy subjects for a total of 801 initial and final contacts. Initial and final contacts were detected with low average errors of (about 20 ms and 10 ms, respectively). Similarly, the errors in estimating stance duration and step duration averaged 20 ms and <10 ms, respectively. By selecting appropriate thresholds, the method may be easily applied to other pressure insoles featuring similar requirements.
准确识别初始和最终的足触地是获取可靠步态时空参数估计的关键前提。该领域公认的黄金标准技术是力台和步态分析系统，它们提供了对地面反作用力的直接测量。然而，这些工具昂贵、不便于携带，并且将分析限制在实验室环境中。具有较少压力感应元件的足底压力传感器鞋垫可能会克服这些限制，但尚未采用适合的步态事件识别方法。本文旨在介绍并验证一种方法，该方法旨在填补这一空白，并将其应用于包括两个具有 16 个压力感应元件（元件面积为 310mm）的鞋垫的系统中，采样频率为 100Hz。利用传感器冗余和基于聚类的策略来识别步态事件。该方法在实验室中通过与力台进行了 9 名健康受试者共 801 次初始和最终足触地的对比测试。初始和最终足触地的检测平均误差较小（分别约为 20ms 和 10ms）。同样，估计支撑期和步幅时间的误差平均分别为 20ms 和<10ms。通过选择适当的阈值，该方法可以轻松应用于具有类似要求的其他足底压力传感器鞋垫。
