Biomedical Engineering Graduate Group, University of California, Davis, Davis, CA 95616, USA.
Department of Neurobiology, Physiology and Behavior, University of California, Davis, Davis, CA 95616, USA.
Sensors (Basel). 2023 May 24;23(11):5022. doi: 10.3390/s23115022.
We evaluated 18 methods capable of identifying initial contact (IC) and terminal contact (TC) gait events during human running using data from a single wearable sensor on the shank or sacrum. We adapted or created code to automatically execute each method, then applied it to identify gait events from 74 runners across different foot strike angles, surfaces, and speeds. To quantify error, estimated gait events were compared to ground truth events from a time-synchronized force plate. Based on our findings, to identify gait events with a wearable on the shank, we recommend the Purcell or Fadillioglu method for IC (biases +17.4 and -24.3 ms; LOAs -96.8 to +131.6 and -137.0 to +88.4 ms) and the Purcell method for TC (bias +3.5 ms; LOAs -143.9 to +150.9 ms). To identify gait events with a wearable on the sacrum, we recommend the Auvinet or Reenalda method for IC (biases -30.4 and +29.0 ms; LOAs -149.2 to +88.5 and -83.3 to +141.3 ms) and the Auvinet method for TC (bias -2.8 ms; LOAs -152.7 to +147.2 ms). Finally, to identify the foot in contact with the ground when using a wearable on the sacrum, we recommend the Lee method (81.9% accuracy).
我们评估了 18 种方法，这些方法能够使用安装在小腿或骶骨上的单个可穿戴传感器来识别人类跑步时的初始接触 (IC) 和终端接触 (TC) 步态事件。我们改编或创建了代码来自动执行每种方法，然后将其应用于识别来自不同足触角度、表面和速度的 74 名跑步者的步态事件。为了量化误差，估计的步态事件与来自时间同步力板的地面真实事件进行了比较。根据我们的发现，要使用小腿上的可穿戴设备识别步态事件，我们建议使用 Purcell 或 Fadillioglu 方法来识别 IC（偏差为 +17.4 和-24.3 毫秒；LOA 为-96.8 到+131.6 和-137.0 到+88.4 毫秒），以及 Purcell 方法来识别 TC（偏差+3.5 毫秒；LOA 为-143.9 到+150.9 毫秒）。要使用骶骨上的可穿戴设备识别步态事件，我们建议使用 Auvinet 或 Reenalda 方法来识别 IC（偏差为-30.4 和+29.0 毫秒；LOA 为-149.2 到+88.5 和-83.3 到+141.3 毫秒），以及 Auvinet 方法来识别 TC（偏差-2.8 毫秒；LOA 为-152.7 到+147.2 毫秒）。最后，要使用骶骨上的可穿戴设备识别与地面接触的脚，我们建议使用 Lee 方法（准确率为 81.9%）。
