IEEE Trans Biomed Eng. 2024 Oct;71(10):2854-2865. doi: 10.1109/TBME.2024.3396650. Epub 2024 Sep 19.
In recent years, radar technology has been extensively utilized in contactless human behavior monitoring systems. The unique capabilities of ultra-wideband (UWB) radars compared to conventional radar technologies, due to time-of-flight measurements, present new untapped opportunities for in-depth monitoring of human movement during overground locomotion. This study aims to investigate the deployability of UWB radars in accurately capturing the gait patterns of healthy individuals with no known walking impairments.
A novel algorithm was developed that can extract ten clinical spatiotemporal gait features using the Doppler information captured from three monostatic UWB radar sensors during a 6-meter walking task. Key gait events are detected from lower-extremity movements based on the joint range-Doppler-time representation of recorded radar data. The estimated gait parameters were validated against a gold-standard optical motion tracking system using 12 healthy volunteers.
On average, nine gait parameters can be consistently estimated with 90-98% accuracy, while capturing 94.5% of participants' gait variability and 90.8% of inter-limb symmetry. Correlation and Bland-Altman analysis revealed a strong correlation between radar-based parameters and the ground-truth values, with average discrepancies consistently close to 0.
Results prove that radar sensing can provide accurate biomarkers to supplement clinical human gait analysis, with quality similar to gold standard assessment.
Radars can potentially allow a transition from expensive and cumbersome lab-based gait analysis tools toward a completely unobtrusive and affordable solution for in-home deployment, enabling continuous long-term monitoring of individuals for research and healthcare applications.
近年来，雷达技术已广泛应用于非接触式人体行为监测系统。与传统雷达技术相比，超宽带（UWB）雷达由于采用飞行时间测量，具有独特的能力，为深入监测地面运动中的人体运动提供了新的未开发机会。本研究旨在调查 UWB 雷达在准确捕捉无已知行走障碍的健康个体步态模式方面的可部署性。
开发了一种新算法，该算法可以使用三个单基地 UWB 雷达传感器在 6 米步行任务中捕获的多普勒信息提取十个临床时空步态特征。根据记录的雷达数据的关节范围-多普勒-时间表示，从下肢运动中检测关键步态事件。使用 12 名健康志愿者的光学运动跟踪系统对估计的步态参数进行验证。
平均而言，九个步态参数可以以 90-98%的准确度一致估计，同时捕获 94.5%的参与者的步态变异性和 90.8%的肢体间对称性。相关性和 Bland-Altman 分析表明，雷达参数与地面真实值之间存在很强的相关性，平均差异始终接近 0。
结果证明雷达感应可以提供准确的生物标志物来补充临床人体步态分析，其质量与黄金标准评估相似。
雷达有可能使人们从昂贵且繁琐的基于实验室的步态分析工具过渡到完全不引人注目的、经济实惠的家庭部署解决方案，从而为研究和医疗保健应用实现对个体的连续长期监测。
