Avellar Leticia M, Leal-Junior Arnaldo G, Diaz Camilo A R, Marques Carlos, Frizera Anselmo
Graduate Program in Electrical Engineering, Federal University of Espirito Santo, Vitoria 29075-910, Brazil.
Mechanical Engineering Department, Federal University of Espirito Santo, Espirito Santo 29075-910, Brazil.
Sensors (Basel). 2019 Jul 31;19(15):3356. doi: 10.3390/s19153356.
This paper presents the development of a smart carpet based on polymer optical fiber (POF) for ground reaction force (GRF) and spatio-temporal gait parameter assessment. The proposed carpet has 20 intensity variation-based sensors on one fiber with two photodetectors for acquisition, each one for the response of 10 closer sensors. The used multiplexing technique is based on side-coupling between the light sources and POF lateral sections in which one light-emitting diode (LED) is activated at a time, sequentially. Three tests were performed, two for sensor characterization and one for validation of the smart carpet, where the first test consisted of the application of calibrated weights on the top of each sensor for force characterization. In the second test, the foot was positioned on predefined points distributed on the carpet, where a mean relative error of 2.9% was obtained. Results of the walking tests on the proposed POF-embedded smart carpet showed the possibility of estimating the GRF and spatio-temporal gait parameters (step and stride lengths, cadence, and stance duration). The obtained results make possible the identification of gait events (stance and swing phases) as well as the stance duration and double support periods. The proposed carpet is a low-cost and reliable tool for gait analysis in different applications.
本文介绍了一种基于聚合物光纤（POF）的智能地毯的开发，用于地面反作用力（GRF）和时空步态参数评估。所提出的地毯在一根光纤上有20个基于强度变化的传感器，配有两个用于采集的光电探测器，每个光电探测器负责10个相邻传感器的响应。所采用的复用技术基于光源与POF横向部分之间的侧面耦合，其中一个发光二极管（LED）一次被顺序激活。进行了三项测试，两项用于传感器特性表征，一项用于智能地毯的验证，其中第一项测试包括在每个传感器顶部施加校准重量以进行力的表征。在第二项测试中，将脚放置在地毯上分布的预定义点上，获得的平均相对误差为2.9%。在所提出的嵌入POF的智能地毯上进行的行走测试结果表明，有可能估计GRF和时空步态参数（步长和步幅、步频和站立持续时间）。所获得的结果使得识别步态事件（站立和摆动阶段）以及站立持续时间和双支撑期成为可能。所提出的地毯是一种低成本且可靠的工具，可用于不同应用中的步态分析。
