M2H/EUROMOV Laboratory, University of Montpellier 1, Montpellier 34090, France.
Sensors (Basel). 2013 Dec 27;14(1):370-81. doi: 10.3390/s140100370.
The present study was aimed at evaluating the Empirical Mode Decomposition (EMD) method to estimate the 3D orientation of the lower trunk during walking using the angular velocity signals generated by a wearable inertial measurement unit (IMU) and notably flawed by drift. The IMU was mounted on the lower trunk (L4-L5) with its active axes aligned with the relevant anatomical axes. The proposed method performs an offline analysis, but has the advantage of not requiring any parameter tuning. The method was validated in two groups of 15 subjects, one during overground walking, with 180° turns, and the other during treadmill walking, both for steady-state and transient speeds, using stereophotogrammetric data. Comparative analysis of the results showed that the IMU/EMD method is able to successfully detrend the integrated angular velocities and estimate lateral bending, flexion-extension as well as axial rotations of the lower trunk during walking with RMS errors of 1 deg for straight walking and lower than 2.5 deg for walking with turns.
本研究旨在评估经验模态分解（EMD）方法，使用可穿戴惯性测量单元（IMU）产生的角速度信号来估计行走时下躯干的 3D 方向，而这些角速度信号显然存在漂移问题。IMU 安装在下躯干（L4-L5）上，其活动轴与相关解剖轴对齐。所提出的方法进行离线分析，但具有无需任何参数调整的优点。该方法在两组 15 名受试者中进行了验证，一组在地面上行走并进行 180°转弯，另一组在跑步机上行走，分别在稳态和瞬态速度下使用立体摄影测量数据进行验证。结果的比较分析表明，IMU/EMD 方法能够成功地去除积分角速度的趋势，并估计下躯干在行走过程中的侧向弯曲、屈伸和轴向旋转，在直走时的均方根误差为 1 度，在转弯时小于 2.5 度。
