Gerontechnology & Rehabilitation Group, University of Bern, 3008 Bern, Switzerland.
Sensors (Basel). 2021 Sep 16;21(18):6205. doi: 10.3390/s21186205.
Gait analysis is an important part of assessments for a variety of health conditions, specifically neurodegenerative diseases. Currently, most methods for gait assessment are based on manual scoring of certain tasks or restrictive technologies. We present an unobtrusive sensor system based on light detection and ranging sensor technology for use in home-like environments. In our evaluation, we compared six different gait parameters, based on recordings from 25 different people performing eight different walks each, resulting in 200 unique measurements. We compared the proposed sensor system against two state-of-the art technologies, a pressure mat and a set of inertial measurement unit sensors. In addition to test usability and long-term measurement, multi-hour recordings were conducted. Our evaluation showed very high correlation (r>0.95) with the gold standards across all assessed gait parameters except for cycle time (r=0.91). Similarly, the coefficient of determination was high (R2>0.9) for all gait parameters except cycle time. The highest correlation was achieved for stride length and velocity (r≥0.98,R2≥0.95). Furthermore, the multi-hour recordings did not show the systematic drift of measurements over time. Overall, the unobtrusive gait measurement system allows for contactless, highly accurate long- and short-term assessments of gait in home-like environments.
步态分析是评估各种健康状况（特别是神经退行性疾病）的重要组成部分。目前，大多数步态评估方法都是基于对某些任务的手动评分或受限技术。我们提出了一种基于光检测和测距传感器技术的非侵入式传感器系统，用于类似于家庭的环境中。在我们的评估中，我们比较了六种不同的步态参数，这些参数是基于 25 个不同的人进行的 8 种不同行走方式的记录，共产生了 200 个独特的测量值。我们将提出的传感器系统与两种最先进的技术（压力垫和一组惯性测量单元传感器）进行了比较。除了测试可用性和长期测量外，还进行了多小时的记录。我们的评估结果表明，除了周期时间（r=0.91）之外，所有评估的步态参数都与黄金标准高度相关（r>0.95）。同样，除了周期时间之外，所有步态参数的决定系数都很高（R2>0.9）。步长和速度的相关性最高（r≥0.98，R2≥0.95）。此外，多小时的记录没有显示出测量值随时间的系统漂移。总体而言，非侵入式步态测量系统允许在类似于家庭的环境中进行非接触式、高度准确的长期和短期步态评估。
