论文标题
使用可穿戴式惯性传感器计数降低的距离测量值估算下肢运动学
Estimating Lower Limb Kinematics using Distance Measurements with a Reduced Wearable Inertial Sensor Count
论文作者
论文摘要
本文提出了一种算法，该算法在距离卡尔曼滤波器旁边的距离测量中进行了新颖的使用，以准确估计骨盆，大腿和柄运动学在步行和其他身体运动过程中仅使用三个可穿戴的惯性测量单元（IMU）。距离测量公式还假定铰链膝关节和恒定的身体片段长度，有助于产生与约束空间相近或在约束空间中的估计值，以获得更好的估计器稳定性。模拟实验表明，IMU间距离测量确实是一种有希望的新信息来源，可以在降低的传感器计数配置下改善惯性运动捕获系统的姿势估计。此外，实验表明，即使在高噪声水平下（例如，$σ_{dist} = 0.2 $ m），动态运动的性能也显着提高，并且在$σ_{dist} = 0.1 $ m处实现正常步行的可接受性能。然而，建议使用实际距离测量传感器进一步验证。
This paper presents an algorithm that makes novel use of distance measurements alongside a constrained Kalman filter to accurately estimate pelvis, thigh, and shank kinematics for both legs during walking and other body movements using only three wearable inertial measurement units (IMUs). The distance measurement formulation also assumes hinge knee joint and constant body segment length, helping produce estimates that are near or in the constraint space for better estimator stability. Simulated experiments shown that inter-IMU distance measurement is indeed a promising new source of information to improve the pose estimation of inertial motion capture systems under a reduced sensor count configuration. Furthermore, experiments show that performance improved dramatically for dynamic movements even at high noise levels (e.g., $σ_{dist} = 0.2$ m), and that acceptable performance for normal walking was achieved at $σ_{dist} = 0.1$ m. Nevertheless, further validation is recommended using actual distance measurement sensors.
