Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.
Sensors (Basel). 2024 Feb 24;24(5):1480. doi: 10.3390/s24051480.
Motion reconstruction using wearable sensors enables broad opportunities for gait analysis outside laboratory environments. Inertial Measurement Unit (IMU)-based foot trajectory reconstruction is an essential component of estimating the foot motion and user position required for any related biomechanics metrics. However, limitations remain in the reconstruction quality due to well-known sensor noise and drift issues, and in some cases, limited sensor bandwidth and range. In this work, to reduce drift in the height direction and handle the impulsive velocity error at heel strike, we enhanced the integration reconstruction with a novel kinematic model that partitions integration velocity errors into estimates of acceleration bias and heel strike vertical velocity error. Using this model, we achieve reduced height drift in reconstruction and simultaneously accomplish reliable terrain determination among level ground, ramps, and stairs. The reconstruction performance of the proposed method is compared against the widely used Error State Kalman Filter-based Pedestrian Dead Reckoning and integration-based foot-IMU motion reconstruction method with 15 trials from six subjects, including one prosthesis user. The mean height errors per stride are 0.03±0.08 cm on level ground, 0.95±0.37 cm on ramps, and 1.27±1.22 cm on stairs. The proposed method can determine the terrain types accurately by thresholding on the model output and demonstrates great reconstruction improvement in level-ground walking and moderate improvement on ramps and stairs.
使用可穿戴传感器进行运动重建为在实验室环境之外进行步态分析提供了广泛的机会。基于惯性测量单元 (IMU) 的足轨迹重建是估计足部运动和用户位置所必需的，这是任何相关生物力学指标所必需的。然而，由于众所周知的传感器噪声和漂移问题，以及在某些情况下传感器带宽和范围有限，重建质量仍然存在限制。在这项工作中，为了减少高度方向的漂移并处理脚跟撞击时的脉冲速度误差，我们通过一种新的运动学模型增强了积分重建，该模型将积分速度误差划分为加速度偏差和脚跟撞击垂直速度误差的估计值。使用这种模型，我们实现了重建中高度漂移的减少，同时在平地、斜坡和楼梯之间可靠地确定地形。与广泛使用的基于误差状态卡尔曼滤波的行人航位推算和基于集成的足部 IMU 运动重建方法相比，该方法在六个受试者（包括一个假肢使用者）的 15 次试验中的重建性能。在平地每步的平均高度误差为 0.03±0.08cm，在斜坡上为 0.95±0.37cm，在楼梯上为 1.27±1.22cm。该方法可以通过模型输出的阈值准确地确定地形类型，并且在平地行走中具有很好的重建改进，在斜坡和楼梯上也有适度的改进。
