Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
Industrial and Operations Engineering, University of Michigan, 1205 Beal Avenue, Ann Arbor, MI 48109, USA.
Sensors (Basel). 2022 Mar 26;22(7):2544. doi: 10.3390/s22072544.
Traditionally, inertial measurement unit (IMU)-based human joint angle estimation techniques are evaluated for general human motion where human joints explore all of their degrees of freedom. Pure human walking, in contrast, limits the motion of human joints and may lead to unobservability conditions that confound magnetometer-free IMU-based methods. This work explores the unobservability conditions emergent during human walking and expands upon a previous IMU-based method for the human knee to also estimate human hip angles relative to an assumed vertical datum. The proposed method is evaluated (N=12) in a human subject study and compared against an optical motion capture system. Accuracy of human knee flexion/extension angle (7.87∘ absolute root mean square error (RMSE)), hip flexion/extension angle (3.70∘ relative RMSE), and hip abduction/adduction angle (4.56∘ relative RMSE) during walking are similar to current state-of-the-art self-calibrating IMU methods that use magnetometers. Larger errors of hip internal/external rotation angle (6.27∘ relative RMSE) are driven by IMU heading drift characteristic of magnetometer-free approaches and non-hinge kinematics of the hip during gait, amongst other error sources. One of these sources of error, soft tissue perturbations during gait, is explored further in the context of knee angle estimation and it was observed that the IMU method may overestimate the angle during stance and underestimate the angle during swing. The presented method and results provide a novel combination of observability considerations, heuristic correction methods, and validation techniques to magnetic-blind, kinematic-only IMU-based skeletal pose estimation during human tasks with degenerate kinematics (e.g., straight line walking).
传统上，基于惯性测量单元（IMU）的人体关节角度估计技术是在人体关节探索其所有自由度的一般人体运动中进行评估的。相比之下，纯粹的人类步行限制了人体关节的运动，并且可能导致混淆无磁强计的基于 IMU 的方法的不可观测条件。这项工作探讨了在人类行走过程中出现的不可观测条件，并扩展了以前基于 IMU 的方法，以估计相对于假定垂直基准的人体髋关节角度。所提出的方法在人体受试者研究中进行了评估（N=12），并与光学运动捕捉系统进行了比较。在行走过程中，人体膝关节屈伸角度（7.87∘绝对均方根误差（RMSE））、髋关节屈伸角度（3.70∘相对 RMSE）和髋关节外展/内收角度（4.56∘相对 RMSE）的准确性与当前使用磁强计的最先进的自校准 IMU 方法相似。髋关节内/外旋转角度（6.27∘相对 RMSE）的较大误差是由无磁强计方法的 IMU 航向漂移特征和步态中髋关节的非铰链运动等误差源驱动的。这些误差源之一，即步态过程中的软组织扰动，在膝关节角度估计的背景下进一步探讨，结果观察到 IMU 方法在站立阶段可能高估角度，在摆动阶段可能低估角度。所提出的方法和结果提供了一种新颖的组合，包括可观测性考虑、启发式校正方法和验证技术，用于在具有退化运动学（例如，直线行走）的人体任务中进行无磁强计、仅运动学的基于 IMU 的骨骼姿势估计。
