Naval Health Research Center, San Diego, CA 92106-3521, USA.
Leidos, Inc., La Jolla, CA 92152, USA.
Sensors (Basel). 2024 Oct 16;24(20):6667. doi: 10.3390/s24206667.
The purpose of this paper is to introduce a method of measuring spatiotemporal gait patterns, tibial accelerations, and heart rate that are matched with high resolution geographical terrain features using publicly available data. These methods were demonstrated using data from 218 Marines, who completed loaded outdoor ruck hikes between 5-20 km over varying terrain. Each participant was instrumented with two inertial measurement units (IMUs) and a GPS watch. Custom code synchronized accelerometer and positional data without a priori sensor synchronization, calibrated orientation of the IMUs in the tibial reference frame, detected and separated only periods of walking or running, and computed acceleration and spatiotemporal outcomes. GPS positional data were georeferenced with geographic information system (GIS) maps to extract terrain features such as slope, altitude, and surface conditions. This paper reveals the ease at which similar data can be gathered among relatively large groups of people with minimal setup and automated data processing. The methods described here can be adapted to other populations and similar ground-based activities such as skiing or trail running.
本文旨在介绍一种测量时空步态模式、胫骨加速度和心率的方法,该方法可与使用公开数据的高分辨率地理地形特征相匹配。这些方法是使用 218 名海军陆战队员的数据演示的,这些队员在不同地形上完成了 5-20 公里的负重户外徒步旅行。每个参与者都配备了两个惯性测量单元 (IMU) 和一个 GPS 手表。自定义代码在没有先验传感器同步的情况下同步加速度计和位置数据,校准 IMU 在胫骨参考系中的方向,仅检测和分离行走或跑步的时间段,并计算加速度和时空结果。GPS 位置数据通过地理信息系统 (GIS) 地图进行地理参考,以提取地形特征,如坡度、海拔和表面状况。本文揭示了在最小设置和自动化数据处理的情况下,相对较大的人群中可以轻松收集类似数据。这里描述的方法可以适应其他人群和类似的地面活动,如滑雪或越野跑。