Laboratory of Locomotor Apparatus Bioengineering, Department of Human Movement and Sport Sciences, Università degli Studi di Roma Foro Italico, Piazza Lauro De Bosis, 6, 00135 Rome, Italy.
Gait Posture. 2012 Jan;35(1):138-42. doi: 10.1016/j.gaitpost.2011.08.024. Epub 2011 Nov 1.
The aim of this study was the fine tuning of a Kalman filter with the intent to provide optimal estimates of lower trunk orientation in the frontal and sagittal planes during treadmill walking at different speeds using measured linear acceleration and angular velocity components represented in a local system of reference. Data were simultaneously collected using both an inertial measurement unit (IMU) and a stereophotogrammetric system from three healthy subjects walking on a treadmill at natural, slow and fast speeds. These data were used to estimate the parameters of the Kalman filter that minimized the difference between the trunk orientations provided by the filter and those obtained through stereophotogrammetry. The optimized parameters were then used to process the data collected from a further 15 healthy subjects of both genders and different anthropometry performing the same walking tasks with the aim of determining the robustness of the filter set up. The filter proved to be very robust. The root mean square values of the differences between the angles estimated through the IMU and through stereophotogrammetry were lower than 1.0° and the correlation coefficients between the corresponding curves were greater than 0.91. The proposed filter design can be used to reliably estimate trunk lateral and frontal bending during walking from inertial sensor data. Further studies are needed to determine the filter parameters that are most suitable for other motor tasks.
本研究的目的是对卡尔曼滤波器进行微调，旨在使用局部参考系中测量的线性加速度和角速度分量，为在不同速度下跑步机行走时的躯干下侧在额状面和矢状面的方向提供最佳估计。本研究使用惯性测量单元 (IMU) 和立体摄影测量系统同时从三个健康受试者在跑步机上以自然、慢和快速度行走时收集数据。这些数据用于估计卡尔曼滤波器的参数，该参数可将滤波器提供的躯干方向与立体摄影测量法获得的躯干方向之间的差异最小化。然后，使用优化后的参数处理从另外 15 名不同性别和不同人体测量学的健康受试者收集的数据，目的是确定滤波器设置的稳健性。该滤波器被证明非常稳健。通过 IMU 和立体摄影测量法估计的角度之间的差异的均方根值低于 1.0°，相应曲线之间的相关系数大于 0.91。该滤波器设计可用于从惯性传感器数据可靠地估计行走时躯干的侧向和额状弯曲。需要进一步的研究来确定最适合其他运动任务的滤波器参数。
