Estimating Ground Reaction Force and Center of Pressure Using Low-Cost Wearable Devices.
Estimating Ground Reaction Force and Center of Pressure Using Low-Cost Wearable Devices.
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DOI：
10.1109/tbme.2021.3120346
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发表时间：
2022-04
期刊：
影响因子：
--
通讯作者：
Lee SI
中科院分区：
文献类型：
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作者：
Oubre B;Lane S;Holmes S;Boyer K;Lee SI
地面反作用力（GRF）和压力中心（CoP）的动态监测可以改善对损害移动性的健康状况的管理。装有力敏电阻器（FSR）的鞋垫是一种不显眼、低成本和低功耗的技术，用于在现实环境中对GRF和CoP进行采样。然而，FSR具有可变的响应特性，使得GRF和CoP的估计复杂化。这项研究引入了一个独特的数据分析管道，使GRF和CoP的准确估计，尽管相对不准确的FSR响应。本文还研究了是否包括一个互补的膝盖角度传感器提高估计精度。17名健康受试者配备有六个FSR和基于弦的膝关节角度传感器的鞋垫。受试者在地面力量平台上以自选的慢速、首选速度和快速速度走直线。每种速度重复20次。有监督的机器学习模型估计了体重归一化的GRF和鞋码归一化的CoP，并对其进行了重新缩放以获得GRF和CoP。前后GRF、垂直GRF和前后CoP的估计标准化均方根误差（NRMSE）小于5%。估计中外侧GRF和CoP的NRMSE分别为8.1%和6.4%。膝关节角度相关功能略微改善了GRF估计。尽管FSR数据存在缺陷，但归一化模型准确估计了GRF和CoP。所提出的系统的门诊使用可以实现对各种健康状况的严重程度和进展的客观、纵向监测。
Ambulatory monitoring of ground reaction force (GRF) and center of pressure (CoP) could improve management of health conditions that impair mobility. Insoles instrumented with force-sensitive resistors (FSRs) are an unobtrusive, low-cost, and low-power technology for sampling GRF and CoP in real-world environments. However, FSRs have variable response characteristics that complicate estimation of GRF and CoP. This study introduces a unique data analytic pipeline that enables accurate estimation of GRF and CoP despite relatively inaccurate FSR responses. This paper also investigates whether inclusion of a complementary knee angle sensor improves estimation accuracy. Seventeen healthy subjects were equipped with an insole instrumented with six FSRs and a string-based knee angle sensor. Subjects walked in a straight line at self-selected slow, preferred, and fast speeds over an in-ground force platform. Twenty repetitions were performed for each speed. Supervised machine learning models estimated weight-normalized GRF and shoe size-normalized CoP, which were re-scaled to obtain GRF and CoP. Anteroposterior GRF, Vertical GRF, and Anteroposterior CoP were estimated with a normalized root mean square error (NRMSE) of less than 5%. Mediolateral GRF and CoP were estimated with an NRMSE of 8.1% and 6.4%, respectively. Knee angle-related features slightly improved GRF estimates. Normalized models accurately estimated GRF and CoP despite deficiencies in FSR data. Ambulatory use of the proposed system could enable objective, longitudinal monitoring of severity and progression for a variety of health conditions.